From 51c76ff4da1a0723f3c25e68ac916457e660b123 Mon Sep 17 00:00:00 2001
From: Sven Klaassen <47529404+SvenKlaassen@users.noreply.github.com>
Date: Wed, 9 Oct 2024 12:58:04 +0200
Subject: [PATCH 01/58] first script for sharp rdd

---
 scripts/rdd/rdd_sharp_coverage.py | 157 ++++++++++++++++++++++++++++++
 1 file changed, 157 insertions(+)
 create mode 100644 scripts/rdd/rdd_sharp_coverage.py

diff --git a/scripts/rdd/rdd_sharp_coverage.py b/scripts/rdd/rdd_sharp_coverage.py
new file mode 100644
index 0000000..a0de46a
--- /dev/null
+++ b/scripts/rdd/rdd_sharp_coverage.py
@@ -0,0 +1,157 @@
+import numpy as np
+import pandas as pd
+from datetime import datetime
+import time
+import sys
+
+from lightgbm import LGBMRegressor, LGBMClassifier
+from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier, StackingRegressor, StackingClassifier
+from sklearn.linear_model import LinearRegression, LassoCV, LogisticRegressionCV, RidgeCV, LogisticRegression
+from rdrobust import rdrobust
+
+import doubleml as dml
+from doubleml.rdd import RDFlex
+from doubleml.rdd.datasets import make_simple_rdd_data
+from doubleml.utils import GlobalRegressor, GlobalClassifier
+
+from statsmodels.nonparametric.kernel_regression import KernelReg
+
+
+# Number of repetitions
+n_rep = 10
+max_runtime = 5.5 * 3600  # 5.5 hours in seconds
+
+# DGP pars
+n_obs = 500
+fuzzy = False
+
+# to get the best possible comparison between different learners (and settings) we first simulate all datasets
+np.random.seed(42)
+
+datasets = []
+for i in range(n_rep):
+    data = make_simple_rdd_data(n_obs=n_obs, fuzzy=fuzzy)
+    datasets.append(data)
+
+# set up hyperparameters
+hyperparam_dict = {
+    "fs_specification": ["cutoff", "cutoff and score", "interacted cutoff and score"],
+    "learner_g": [
+        ("Lasso", LassoCV()),
+        ("Linear", LinearRegression()),
+        ("LGBM", LGBMRegressor(n_estimators=100, max_depth=5, learning_rate=0.1, verbose=-1)),],
+    "level": [0.95, 0.90]}
+
+# set up the results dataframe
+df_results_detailed = pd.DataFrame()
+
+# start simulation
+np.random.seed(42)
+start_time = time.time()
+
+for i_rep in range(n_rep):
+    print(f"Repetition: {i_rep}/{n_rep}", end="\r")
+
+    # Check the elapsed time
+    elapsed_time = time.time() - start_time
+    if elapsed_time > max_runtime:
+        print("Maximum runtime exceeded. Stopping the simulation.")
+        break
+
+    # get oracle value
+    score = data["score"]
+    ite = data["oracle_values"]['Y1'] - data["oracle_values"]['Y0']
+
+    kernel_reg = KernelReg(endog=ite, exog=score, var_type='c', reg_type='ll')
+    cutoff = 0
+
+    effect_at_cutoff, _ = kernel_reg.fit(np.array([cutoff]))
+    oracle_effect = effect_at_cutoff[0]
+
+    Y = data["Y"]
+    Z = data["X"].reshape(n_obs, -1)
+    D = data["D"]
+
+    # baseline
+    for level_idx, level in enumerate(hyperparam_dict["level"]):
+        res = rdrobust(y=Y, x=score, fuzzy=D, covs=Z, c=cutoff, level=level*100)
+        coef = res.coef.loc["Conventional", "Coeff"]
+        ci_lower = res.ci.loc["Robust", "CI Lower"]
+        ci_upper = res.ci.loc["Robust", "CI Upper"]
+
+        coverage = (ci_lower < oracle_effect) & (oracle_effect < ci_upper)
+        ci_length = ci_upper - ci_lower
+
+        df_results_detailed = pd.concat(
+            (df_results_detailed,
+                pd.DataFrame({
+                    "Coverage": coverage.astype(int),
+                    "CI Length": ci_length,
+                    "Bias": abs(coef - oracle_effect),
+                    "Learner g": "linear",
+                    "Method": "rdrobust",
+                    "fs specification": "interacted cutoff and score",
+                    "level": level,
+                    "repetition": i_rep}, index=[0])),
+            ignore_index=True)
+
+    # define the DoubleML data object
+    obj_dml_data = dml.DoubleMLData.from_arrays(y=Y, d=D, x=Z, s=score)
+
+    for learner_g_idx, (learner_g_name, ml_g) in enumerate(hyperparam_dict["learner_g"]):
+        for fs_specification_idx, fs_specification in enumerate(hyperparam_dict["fs_specification"]):
+            rdflex_model = RDFlex(
+                obj_dml_data,
+                ml_g=ml_g,
+                n_folds=5,
+                n_rep=1,
+                cutoff=cutoff,
+                fuzzy=False,
+                fs_specification=fs_specification)
+            rdflex_model.fit(n_iterations=2)
+
+            for level_idx, level in enumerate(hyperparam_dict["level"]):
+                confint = rdflex_model.confint(level=level)
+                coverage = (confint.iloc[0, 0] < oracle_effect) & (oracle_effect < confint.iloc[0, 1])
+                ci_length = confint.iloc[0, 1] - confint.iloc[0, 0]
+
+                df_results_detailed = pd.concat(
+                    (df_results_detailed,
+                        pd.DataFrame({
+                            "Coverage": coverage.astype(int),
+                            "CI Length": confint.iloc[0, 1] - confint.iloc[0, 0],
+                            "Bias": abs(rdflex_model.coef[0] - oracle_effect),
+                            "Learner g": learner_g_name,
+                            "Method": "rdflex",
+                            "fs specification": fs_specification,
+                            "level": level,
+                            "repetition": i_rep}, index=[0])),
+                    ignore_index=True)
+
+df_results = df_results_detailed.groupby(
+    ["Method", "fs specification", "Learner g", "level"]).agg(
+        {"Coverage": "mean",
+         "CI Length": "mean",
+         "Bias": "mean",
+         "repetition": "count"}
+    ).reset_index()
+print(df_results)
+
+end_time = time.time()
+total_runtime = end_time - start_time
+
+# save results
+script_name = "rdd_sharp_coverage.py"
+path = "results/rdd/rdd_sharp_coverage"
+
+metadata = pd.DataFrame({
+    'DoubleML Version': [dml.__version__],
+    'Script': [script_name],
+    'Date': [datetime.now().strftime("%Y-%m-%d %H:%M:%S")],
+    'Total Runtime (seconds)': [total_runtime],
+    'Python Version': [f"{sys.version_info.major}.{sys.version_info.minor}.{sys.version_info.micro}"],
+})
+print(metadata)
+
+df_results.to_csv(f"{path}.csv", index=False)
+metadata.to_csv(f"{path}_metadata.csv", index=False)

From 734d20b3ba724b75dcf21075e32ad9b75d2d3301 Mon Sep 17 00:00:00 2001
From: Sven Klaassen <47529404+SvenKlaassen@users.noreply.github.com>
Date: Wed, 9 Oct 2024 14:32:34 +0200
Subject: [PATCH 02/58] add rdd scripts

---
 scripts/rdd/rdd_fuzzy_coverage.py | 178 ++++++++++++++++++++++++++++++
 scripts/rdd/rdd_sharp_coverage.py |  22 ++--
 2 files changed, 192 insertions(+), 8 deletions(-)
 create mode 100644 scripts/rdd/rdd_fuzzy_coverage.py

diff --git a/scripts/rdd/rdd_fuzzy_coverage.py b/scripts/rdd/rdd_fuzzy_coverage.py
new file mode 100644
index 0000000..a7ef02e
--- /dev/null
+++ b/scripts/rdd/rdd_fuzzy_coverage.py
@@ -0,0 +1,178 @@
+import numpy as np
+import pandas as pd
+from datetime import datetime
+import time
+import sys
+
+from lightgbm import LGBMRegressor, LGBMClassifier
+from sklearn.ensemble import StackingRegressor, StackingClassifier
+from sklearn.linear_model import LinearRegression, Ridge, LogisticRegression
+from rdrobust import rdrobust
+
+import doubleml as dml
+from doubleml.rdd import RDFlex
+from doubleml.rdd.datasets import make_simple_rdd_data
+from doubleml.utils import GlobalRegressor, GlobalClassifier
+
+from statsmodels.nonparametric.kernel_regression import KernelReg
+
+
+# Number of repetitions
+n_rep = 100
+max_runtime = 5.5 * 3600  # 5.5 hours in seconds
+
+# DGP pars
+n_obs = 500
+fuzzy = True
+
+# to get the best possible comparison between different learners (and settings) we first simulate all datasets
+np.random.seed(42)
+
+datasets = []
+for i in range(n_rep):
+    data = make_simple_rdd_data(n_obs=n_obs, fuzzy=fuzzy)
+    datasets.append(data)
+
+# set up hyperparameters
+hyperparam_dict = {
+    "fs_specification": ["cutoff", "cutoff and score", "interacted cutoff and score"],
+    "learner_g": [
+        ("Linear", LinearRegression()),
+        ("LGBM", LGBMRegressor(n_estimators=100, max_depth=5, learning_rate=0.1, verbose=-1)),
+        ("Global linear", GlobalRegressor(LinearRegression())),
+        ("Stacked", StackingRegressor(
+            estimators=[
+                ('lr', LinearRegression()),
+                ('lgbm', LGBMRegressor(n_estimators=100, max_depth=5, learning_rate=0.1, verbose=-1)),
+                ('glr', GlobalRegressor(LinearRegression()))],
+            final_estimator=Ridge()))],
+    "learner_m": [
+        ("Linear", LogisticRegression()),
+        ("LGBM", LGBMClassifier(n_estimators=100, max_depth=5, learning_rate=0.1, verbose=-1)),
+        ("Global linear", GlobalClassifier(LogisticRegression())),
+        ("Stacked", StackingClassifier(
+            estimators=[
+                ('lr', LogisticRegression()),
+                ('lgbm', LGBMClassifier(n_estimators=100, max_depth=5, learning_rate=0.1, verbose=-1)),
+                ('glr', GlobalClassifier(LogisticRegression()))],
+            final_estimator=LogisticRegression()))],
+    "level": [0.95, 0.90]}
+
+# set up the results dataframe
+df_results_detailed = pd.DataFrame()
+
+# start simulation
+np.random.seed(42)
+start_time = time.time()
+
+for i_rep in range(n_rep):
+    print(f"Repetition: {i_rep}/{n_rep}", end="\r")
+
+    # Check the elapsed time
+    elapsed_time = time.time() - start_time
+    if elapsed_time > max_runtime:
+        print("Maximum runtime exceeded. Stopping the simulation.")
+        break
+
+    # get oracle value
+    cutoff = 0
+    score = data["score"]
+    complier_mask = (((data["D"] == 0) & (data["score"] < cutoff)) | ((data["D"] == 1) & (data["score"] > cutoff)))
+
+    ite = data["oracle_values"]['Y1'] - data["oracle_values"]['Y0']
+    kernel_reg = KernelReg(endog=ite[complier_mask], exog=score[complier_mask], var_type='c', reg_type='ll')
+
+    effect_at_cutoff, _ = kernel_reg.fit(np.array([cutoff]))
+    oracle_effect = effect_at_cutoff[0]
+
+    Y = data["Y"]
+    Z = data["X"].reshape(n_obs, -1)
+    D = data["D"]
+
+    # baseline
+    for level_idx, level in enumerate(hyperparam_dict["level"]):
+        res = rdrobust(y=Y, x=score, fuzzy=D, covs=Z, c=cutoff, level=level*100)
+        coef = res.coef.loc["Conventional", "Coeff"]
+        ci_lower = res.ci.loc["Robust", "CI Lower"]
+        ci_upper = res.ci.loc["Robust", "CI Upper"]
+
+        coverage = (ci_lower < oracle_effect) & (oracle_effect < ci_upper)
+        ci_length = ci_upper - ci_lower
+
+        df_results_detailed = pd.concat(
+            (df_results_detailed,
+                pd.DataFrame({
+                    "Coverage": coverage.astype(int),
+                    "CI Length": ci_length,
+                    "Bias": abs(coef - oracle_effect),
+                    "Learner g": "linear",
+                    "Learner m": "linear",
+                    "Method": "rdrobust",
+                    "fs specification": "interacted cutoff and score",
+                    "level": level,
+                    "repetition": i_rep}, index=[0])),
+            ignore_index=True)
+
+    # define the DoubleML data object
+    obj_dml_data = dml.DoubleMLData.from_arrays(y=Y, d=D, x=Z, s=score)
+
+    for learner_g_idx, (learner_g_name, ml_g) in enumerate(hyperparam_dict["learner_g"]):
+        for learner_m_idx, (learner_m_name, ml_m) in enumerate(hyperparam_dict["learner_m"]):
+            for fs_specification_idx, fs_specification in enumerate(hyperparam_dict["fs_specification"]):
+                rdflex_model = RDFlex(
+                    obj_dml_data,
+                    ml_g=ml_g,
+                    ml_m=ml_m,
+                    n_folds=5,
+                    n_rep=1,
+                    cutoff=cutoff,
+                    fuzzy=True,
+                    fs_specification=fs_specification)
+                rdflex_model.fit(n_iterations=2)
+
+                for level_idx, level in enumerate(hyperparam_dict["level"]):
+                    confint = rdflex_model.confint(level=level)
+                    coverage = (confint.iloc[0, 0] < oracle_effect) & (oracle_effect < confint.iloc[0, 1])
+                    ci_length = confint.iloc[0, 1] - confint.iloc[0, 0]
+
+                    df_results_detailed = pd.concat(
+                        (df_results_detailed,
+                            pd.DataFrame({
+                                "Coverage": coverage.astype(int),
+                                "CI Length": confint.iloc[0, 1] - confint.iloc[0, 0],
+                                "Bias": abs(rdflex_model.coef[0] - oracle_effect),
+                                "Learner g": learner_g_name,
+                                "Learner m": learner_m_name,
+                                "Method": "rdflex",
+                                "fs specification": fs_specification,
+                                "level": level,
+                                "repetition": i_rep}, index=[0])),
+                        ignore_index=True)
+
+df_results = df_results_detailed.groupby(
+    ["Method", "fs specification", "Learner g", "Learner m", "level"]).agg(
+        {"Coverage": "mean",
+         "CI Length": "mean",
+         "Bias": "mean",
+         "repetition": "count"}
+    ).reset_index()
+print(df_results)
+
+end_time = time.time()
+total_runtime = end_time - start_time
+
+# save results
+script_name = "rdd_fuzzy_coverage.py"
+path = "results/rdd/rdd_fuzzy_coverage"
+
+metadata = pd.DataFrame({
+    'DoubleML Version': [dml.__version__],
+    'Script': [script_name],
+    'Date': [datetime.now().strftime("%Y-%m-%d %H:%M:%S")],
+    'Total Runtime (seconds)': [total_runtime],
+    'Python Version': [f"{sys.version_info.major}.{sys.version_info.minor}.{sys.version_info.micro}"],
+})
+print(metadata)
+
+df_results.to_csv(f"{path}.csv", index=False)
+metadata.to_csv(f"{path}_metadata.csv", index=False)
diff --git a/scripts/rdd/rdd_sharp_coverage.py b/scripts/rdd/rdd_sharp_coverage.py
index a0de46a..9c8dc80 100644
--- a/scripts/rdd/rdd_sharp_coverage.py
+++ b/scripts/rdd/rdd_sharp_coverage.py
@@ -4,21 +4,21 @@
 import time
 import sys
 
-from lightgbm import LGBMRegressor, LGBMClassifier
-from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier, StackingRegressor, StackingClassifier
-from sklearn.linear_model import LinearRegression, LassoCV, LogisticRegressionCV, RidgeCV, LogisticRegression
+from lightgbm import LGBMRegressor
+from sklearn.ensemble import StackingRegressor
+from sklearn.linear_model import LinearRegression, Ridge
 from rdrobust import rdrobust
 
 import doubleml as dml
 from doubleml.rdd import RDFlex
 from doubleml.rdd.datasets import make_simple_rdd_data
-from doubleml.utils import GlobalRegressor, GlobalClassifier
+from doubleml.utils import GlobalRegressor
 
 from statsmodels.nonparametric.kernel_regression import KernelReg
 
 
 # Number of repetitions
-n_rep = 10
+n_rep = 100
 max_runtime = 5.5 * 3600  # 5.5 hours in seconds
 
 # DGP pars
@@ -37,9 +37,15 @@
 hyperparam_dict = {
     "fs_specification": ["cutoff", "cutoff and score", "interacted cutoff and score"],
     "learner_g": [
-        ("Lasso", LassoCV()),
         ("Linear", LinearRegression()),
-        ("LGBM", LGBMRegressor(n_estimators=100, max_depth=5, learning_rate=0.1, verbose=-1)),],
+        ("LGBM", LGBMRegressor(n_estimators=100, max_depth=5, learning_rate=0.1, verbose=-1)),
+        ("Global linear", GlobalRegressor(LinearRegression())),
+        ("Stacked", StackingRegressor(
+            estimators=[
+                ('lr', LinearRegression()),
+                ('lgbm', LGBMRegressor(n_estimators=100, max_depth=5, learning_rate=0.1, verbose=-1)),
+                ('glr', GlobalRegressor(LinearRegression()))],
+            final_estimator=Ridge()))],
     "level": [0.95, 0.90]}
 
 # set up the results dataframe
@@ -74,7 +80,7 @@
 
     # baseline
     for level_idx, level in enumerate(hyperparam_dict["level"]):
-        res = rdrobust(y=Y, x=score, fuzzy=D, covs=Z, c=cutoff, level=level*100)
+        res = rdrobust(y=Y, x=score, covs=Z, c=cutoff, level=level*100)
         coef = res.coef.loc["Conventional", "Coeff"]
         ci_lower = res.ci.loc["Robust", "CI Lower"]
         ci_upper = res.ci.loc["Robust", "CI Upper"]

From 3a77906105666f3d53cc20cbbb39c8e2be541a1b Mon Sep 17 00:00:00 2001
From: Sven Klaassen <47529404+SvenKlaassen@users.noreply.github.com>
Date: Wed, 9 Oct 2024 14:32:59 +0200
Subject: [PATCH 03/58] first site rdd

---
 doc/_quarto.yml |   4 ++
 doc/rdd/rdd.qmd | 145 ++++++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 149 insertions(+)
 create mode 100644 doc/rdd/rdd.qmd

diff --git a/doc/_quarto.yml b/doc/_quarto.yml
index 19ec8e0..583af63 100644
--- a/doc/_quarto.yml
+++ b/doc/_quarto.yml
@@ -34,6 +34,10 @@ website:
         menu:      
           - ssm/ssm_mar.qmd
           - ssm/ssm_nonignorable.qmd
+      - text: "RDD"
+        menu: 
+          - rdd/rdd.qmd
+          
     right: 
       - icon: book
         href: https://docs.doubleml.org/stable/index.html
diff --git a/doc/rdd/rdd.qmd b/doc/rdd/rdd.qmd
new file mode 100644
index 0000000..fff8359
--- /dev/null
+++ b/doc/rdd/rdd.qmd
@@ -0,0 +1,145 @@
+---
+title: "Flexible covariate adjustments in RDD"
+
+jupyter: python3
+---
+
+
+```{python}
+#| echo: false
+
+import numpy as np
+import pandas as pd
+from itables import init_notebook_mode, show, options
+
+init_notebook_mode(all_interactive=True)
+
+def highlight_range(s, level=0.95, dist=0.05, props=''):
+    color_grid = np.where((s >= level-dist) &
+                          (s <= level+dist), props, '')
+    return color_grid
+
+
+def color_coverage(df, level):
+    # color coverage column order is important
+    styled_df = df.apply(
+        highlight_range,
+        level=level,
+        dist=1.0,
+        props='color:black;background-color:red',
+        subset=["Coverage"])
+    styled_df = styled_df.apply(
+        highlight_range,
+        level=level,
+        dist=0.1,
+        props='color:black;background-color:yellow',
+        subset=["Coverage"])
+    styled_df = styled_df.apply(
+        highlight_range,
+        level=level,
+        dist=0.05,
+        props='color:white;background-color:darkgreen',
+        subset=["Coverage"])
+
+    # set all coverage values to bold
+    styled_df = styled_df.set_properties(
+        **{'font-weight': 'bold'},
+        subset=["Coverage"])
+    return styled_df
+
+
+def make_pretty(df, level, n_rep):
+    styled_df = df.style.hide(axis="index")
+    # Format only float columns
+    float_cols = df.select_dtypes(include=['float']).columns
+    styled_df = styled_df.format({col: "{:.3f}" for col in float_cols})
+
+    # color coverage column order is important
+    styled_df = color_coverage(styled_df, level)
+    caption = f"Coverage for {level*100}%-Confidence Interval over {n_rep} Repetitions"
+
+    return show(styled_df, caption=caption)
+```
+
+## Sharp Design
+
+::: {.callout-note title="Metadata"  collapse="true"}
+
+```{python}
+#| echo: false
+metadata_file = '../../results/rdd/rdd_sharp_coverage_metadata.csv'
+metadata_df = pd.read_csv(metadata_file)
+print(metadata_df.T.to_string(header=False))
+```
+
+:::
+
+```{python}
+# | echo: false
+
+# set up data and rename columns
+df = pd.read_csv("../../results/rdd/rdd_sharp_coverage.csv", index_col=None)
+
+assert df["repetition"].nunique() == 1
+n_rep = df["repetition"].unique()[0]
+
+display_columns = ["Method", "Learner g", "fs specification", "Bias", "CI Length", "Coverage"]
+```
+
+```{python}
+#| echo: false
+level = 0.95
+
+df_ate_95 = df[(df['level'] == level)][display_columns]
+make_pretty(df_ate_95, level, n_rep)
+```
+
+```{python}
+#| echo: false
+level = 0.9
+
+df_ate_9 = df[(df['level'] == level)][display_columns]
+make_pretty(df_ate_9, level, n_rep)
+```
+
+
+## Fuzzy Design
+
+::: {.callout-note title="Metadata"  collapse="true"}
+
+```{python}
+#| echo: false
+metadata_file = '../../results/rdd/rdd_fuzzy_coverage_metadata.csv'
+metadata_df = pd.read_csv(metadata_file)
+print(metadata_df.T.to_string(header=False))
+```
+
+:::
+
+```{python}
+# | echo: false
+
+# set up data and rename columns
+df = pd.read_csv("../../results/rdd/rdd_fuzzy_coverage.csv", index_col=None)
+
+assert df["repetition"].nunique() == 1
+n_rep = df["repetition"].unique()[0]
+
+display_columns = ["Method", "Learner g", "Learner m", "fs specification", "Bias", "CI Length", "Coverage"]
+```
+
+```{python}
+#| echo: false
+level = 0.95
+
+df_ate_95 = df[(df['level'] == level)][display_columns]
+make_pretty(df_ate_95, level, n_rep)
+```
+
+```{python}
+#| echo: false
+level = 0.9
+
+df_ate_9 = df[(df['level'] == level)][display_columns]
+make_pretty(df_ate_9, level, n_rep)
+```
\ No newline at end of file

From 843a4a1f8402fbf3aa86ebd3029de935577be6ac Mon Sep 17 00:00:00 2001
From: Sven Klaassen <47529404+SvenKlaassen@users.noreply.github.com>
Date: Wed, 9 Oct 2024 17:30:49 +0200
Subject: [PATCH 04/58] first rdd results

---
 results/rdd/rdd_fuzzy_coverage.csv          | 99 +++++++++++++++++++++
 results/rdd/rdd_fuzzy_coverage_metadata.csv |  2 +
 results/rdd/rdd_sharp_coverage.csv          | 27 ++++++
 results/rdd/rdd_sharp_coverage_metadata.csv |  2 +
 scripts/rdd/rdd_fuzzy_coverage.py           |  1 +
 scripts/rdd/rdd_sharp_coverage.py           |  1 +
 6 files changed, 132 insertions(+)
 create mode 100644 results/rdd/rdd_fuzzy_coverage.csv
 create mode 100644 results/rdd/rdd_fuzzy_coverage_metadata.csv
 create mode 100644 results/rdd/rdd_sharp_coverage.csv
 create mode 100644 results/rdd/rdd_sharp_coverage_metadata.csv

diff --git a/results/rdd/rdd_fuzzy_coverage.csv b/results/rdd/rdd_fuzzy_coverage.csv
new file mode 100644
index 0000000..10a864c
--- /dev/null
+++ b/results/rdd/rdd_fuzzy_coverage.csv
@@ -0,0 +1,99 @@
+Method,fs specification,Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
+rdflex,cutoff,Global linear,Global linear,0.9,1.0,24576.052985663362,33.714993058400886,100
+rdflex,cutoff,Global linear,Global linear,0.95,1.0,29284.173342111826,33.714993058400886,100
+rdflex,cutoff,Global linear,LGBM,0.9,1.0,212.7670843346672,7.394068380531208,100
+rdflex,cutoff,Global linear,LGBM,0.95,1.0,253.52761823824412,7.394068380531208,100
+rdflex,cutoff,Global linear,Linear,0.9,1.0,7285.560991813301,25.24811183810531,100
+rdflex,cutoff,Global linear,Linear,0.95,1.0,8681.281371880557,25.24811183810531,100
+rdflex,cutoff,Global linear,Stacked,0.9,1.0,394.455579919443,9.344964372631935,100
+rdflex,cutoff,Global linear,Stacked,0.95,1.0,470.02281386936954,9.344964372631935,100
+rdflex,cutoff,LGBM,Global linear,0.9,0.99,72.60636323582686,2.7988886732167635,100
+rdflex,cutoff,LGBM,Global linear,0.95,1.0,86.51581797852712,2.7988886732167635,100
+rdflex,cutoff,LGBM,LGBM,0.9,0.99,96.8467863259473,3.616213865899996,100
+rdflex,cutoff,LGBM,LGBM,0.95,1.0,115.40006363308038,3.616213865899996,100
+rdflex,cutoff,LGBM,Linear,0.9,1.0,502.9674323275353,4.744361836099421,100
+rdflex,cutoff,LGBM,Linear,0.95,1.0,599.3226610598828,4.744361836099421,100
+rdflex,cutoff,LGBM,Stacked,0.9,0.97,30.402335642968584,2.136680518057323,100
+rdflex,cutoff,LGBM,Stacked,0.95,1.0,36.22661732919947,2.136680518057323,100
+rdflex,cutoff,Linear,Global linear,0.9,1.0,288.2129055526289,6.8505494565519385,100
+rdflex,cutoff,Linear,Global linear,0.95,1.0,343.42685908760353,6.8505494565519385,100
+rdflex,cutoff,Linear,LGBM,0.9,1.0,1267.7114353254287,11.7553962645311,100
+rdflex,cutoff,Linear,LGBM,0.95,1.0,1510.571345264586,11.7553962645311,100
+rdflex,cutoff,Linear,Linear,0.9,1.0,450781.6204890172,106.12716308132217,100
+rdflex,cutoff,Linear,Linear,0.95,1.0,537139.4308735916,106.12716308132217,100
+rdflex,cutoff,Linear,Stacked,0.9,1.0,881.7068963348019,9.734537855926657,100
+rdflex,cutoff,Linear,Stacked,0.95,1.0,1050.6185677686365,9.734537855926657,100
+rdflex,cutoff,Stacked,Global linear,0.9,0.97,1290.6705810610117,5.997544912636781,100
+rdflex,cutoff,Stacked,Global linear,0.95,1.0,1537.92885478411,5.997544912636781,100
+rdflex,cutoff,Stacked,LGBM,0.9,1.0,136.62140422287027,3.333628982473081,100
+rdflex,cutoff,Stacked,LGBM,0.95,1.0,162.7944440809591,3.333628982473081,100
+rdflex,cutoff,Stacked,Linear,0.9,0.97,1428.1853101775168,6.810519084378244,100
+rdflex,cutoff,Stacked,Linear,0.95,1.0,1701.7877611304823,6.810519084378244,100
+rdflex,cutoff,Stacked,Stacked,0.9,0.97,31.755052523109708,2.457304897883856,100
+rdflex,cutoff,Stacked,Stacked,0.95,1.0,37.838478909411805,2.457304897883856,100
+rdflex,cutoff and score,Global linear,Global linear,0.9,1.0,360.03334552320234,9.290898235230898,100
+rdflex,cutoff and score,Global linear,Global linear,0.95,1.0,429.00619173438497,9.290898235230898,100
+rdflex,cutoff and score,Global linear,LGBM,0.9,1.0,65.141857558003,5.866315242081892,100
+rdflex,cutoff and score,Global linear,LGBM,0.95,1.0,77.62131086177858,5.866315242081892,100
+rdflex,cutoff and score,Global linear,Linear,0.9,1.0,188.2737747038422,7.579674700252163,100
+rdflex,cutoff and score,Global linear,Linear,0.95,1.0,224.3420396846204,7.579674700252163,100
+rdflex,cutoff and score,Global linear,Stacked,0.9,1.0,101.09651866526238,6.189455751901226,100
+rdflex,cutoff and score,Global linear,Stacked,0.95,1.0,120.46393204818669,6.189455751901226,100
+rdflex,cutoff and score,LGBM,Global linear,0.9,0.97,73.65691077194248,3.3577859423993432,100
+rdflex,cutoff and score,LGBM,Global linear,0.95,1.0,87.76762257748713,3.3577859423993432,100
+rdflex,cutoff and score,LGBM,LGBM,0.9,0.98,906.6323063282008,6.052558120730604,100
+rdflex,cutoff and score,LGBM,LGBM,0.95,1.0,1080.3190256613543,6.052558120730604,100
+rdflex,cutoff and score,LGBM,Linear,0.9,0.97,704.8526691961484,5.409173897890411,100
+rdflex,cutoff and score,LGBM,Linear,0.95,0.99,839.8837582841852,5.409173897890411,100
+rdflex,cutoff and score,LGBM,Stacked,0.9,0.99,209.1865557589259,3.8332926812316845,100
+rdflex,cutoff and score,LGBM,Stacked,0.95,1.0,249.26115529036716,3.8332926812316845,100
+rdflex,cutoff and score,Linear,Global linear,0.9,0.99,3016.5600996185135,14.768373929828062,100
+rdflex,cutoff and score,Linear,Global linear,0.95,1.0,3594.4530598814645,14.768373929828062,100
+rdflex,cutoff and score,Linear,LGBM,0.9,1.0,13407.437191137702,29.954023874117556,100
+rdflex,cutoff and score,Linear,LGBM,0.95,1.0,15975.94678884338,29.954023874117556,100
+rdflex,cutoff and score,Linear,Linear,0.9,1.0,159.9589119416921,7.375932003888324,100
+rdflex,cutoff and score,Linear,Linear,0.95,1.0,190.60279971111376,7.375932003888324,100
+rdflex,cutoff and score,Linear,Stacked,0.9,1.0,77.8159882626384,6.6020932037079305,100
+rdflex,cutoff and score,Linear,Stacked,0.95,1.0,92.72346907781267,6.6020932037079305,100
+rdflex,cutoff and score,Stacked,Global linear,0.9,0.99,296.00629012356245,4.83669396654298,100
+rdflex,cutoff and score,Stacked,Global linear,0.95,1.0,352.7132495763485,4.83669396654298,100
+rdflex,cutoff and score,Stacked,LGBM,0.9,0.99,653.7024865250983,5.333034986632671,100
+rdflex,cutoff and score,Stacked,LGBM,0.95,1.0,778.934556364189,5.333034986632671,100
+rdflex,cutoff and score,Stacked,Linear,0.9,0.96,260.69680825739044,4.667422911300441,100
+rdflex,cutoff and score,Stacked,Linear,0.95,1.0,310.6394068729521,4.667422911300441,100
+rdflex,cutoff and score,Stacked,Stacked,0.9,0.98,1028.1581452399262,6.541291874878417,100
+rdflex,cutoff and score,Stacked,Stacked,0.95,1.0,1225.125994230008,6.541291874878417,100
+rdflex,interacted cutoff and score,Global linear,Global linear,0.9,1.0,115.02137421624799,6.955730839588052,100
+rdflex,interacted cutoff and score,Global linear,Global linear,0.95,1.0,137.05642084029714,6.955730839588052,100
+rdflex,interacted cutoff and score,Global linear,LGBM,0.9,1.0,2138.206925338846,13.383695980176464,100
+rdflex,interacted cutoff and score,Global linear,LGBM,0.95,1.0,2547.830698422324,13.383695980176464,100
+rdflex,interacted cutoff and score,Global linear,Linear,0.9,1.0,248.64260039669713,8.933890175218044,100
+rdflex,interacted cutoff and score,Global linear,Linear,0.95,1.0,296.27593228651983,8.933890175218044,100
+rdflex,interacted cutoff and score,Global linear,Stacked,0.9,1.0,7830.074178774233,26.977813963864392,100
+rdflex,interacted cutoff and score,Global linear,Stacked,0.95,1.0,9330.108852978992,26.977813963864392,100
+rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.96,110.87219823076155,3.26608101071588,100
+rdflex,interacted cutoff and score,LGBM,Global linear,0.95,1.0,132.11237271113686,3.26608101071588,100
+rdflex,interacted cutoff and score,LGBM,LGBM,0.9,1.0,20.922562677679036,1.9592975523809535,100
+rdflex,interacted cutoff and score,LGBM,LGBM,0.95,1.0,24.93077112796655,1.9592975523809535,100
+rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.98,93.57449880755165,3.3828798935653133,100
+rdflex,interacted cutoff and score,LGBM,Linear,0.95,1.0,111.50089255911544,3.3828798935653133,100
+rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.98,28.741965545451134,2.508094158883194,100
+rdflex,interacted cutoff and score,LGBM,Stacked,0.95,1.0,34.24816432960168,2.508094158883194,100
+rdflex,interacted cutoff and score,Linear,Global linear,0.9,1.0,20640.141712201705,18.641835328086387,100
+rdflex,interacted cutoff and score,Linear,Global linear,0.95,1.0,24594.245791155576,18.641835328086387,100
+rdflex,interacted cutoff and score,Linear,LGBM,0.9,1.0,298.98997131061145,9.730810172540227,100
+rdflex,interacted cutoff and score,Linear,LGBM,0.95,1.0,356.2685249954775,9.730810172540227,100
+rdflex,interacted cutoff and score,Linear,Linear,0.9,1.0,5006.456402704061,18.416688138138774,100
+rdflex,interacted cutoff and score,Linear,Linear,0.95,1.0,5965.560751843976,18.416688138138774,100
+rdflex,interacted cutoff and score,Linear,Stacked,0.9,1.0,275.5207382066559,10.066409170458378,100
+rdflex,interacted cutoff and score,Linear,Stacked,0.95,1.0,328.30320888781813,10.066409170458378,100
+rdflex,interacted cutoff and score,Stacked,Global linear,0.9,0.97,867.4679612121456,5.903459537041831,100
+rdflex,interacted cutoff and score,Stacked,Global linear,0.95,1.0,1033.6518300836956,5.903459537041831,100
+rdflex,interacted cutoff and score,Stacked,LGBM,0.9,0.97,263.20550887930045,4.132180855975779,100
+rdflex,interacted cutoff and score,Stacked,LGBM,0.95,1.0,313.6287080401628,4.132180855975779,100
+rdflex,interacted cutoff and score,Stacked,Linear,0.9,0.99,85.29228313835699,3.155082488308933,100
+rdflex,interacted cutoff and score,Stacked,Linear,0.95,1.0,101.63202389029637,3.155082488308933,100
+rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.98,23.815976412169956,2.214781308607141,100
+rdflex,interacted cutoff and score,Stacked,Stacked,0.95,0.99,28.378486243193066,2.214781308607141,100
+rdrobust,interacted cutoff and score,linear,linear,0.9,0.99,188.44638549344222,8.674372870881726,100
+rdrobust,interacted cutoff and score,linear,linear,0.95,1.0,224.54771812640732,8.674372870881726,100
diff --git a/results/rdd/rdd_fuzzy_coverage_metadata.csv b/results/rdd/rdd_fuzzy_coverage_metadata.csv
new file mode 100644
index 0000000..56698e5
--- /dev/null
+++ b/results/rdd/rdd_fuzzy_coverage_metadata.csv
@@ -0,0 +1,2 @@
+DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
+0.9.dev0,rdd_fuzzy_coverage.py,2024-10-09 17:19:09,7052.292869091034,3.12.4
diff --git a/results/rdd/rdd_sharp_coverage.csv b/results/rdd/rdd_sharp_coverage.csv
new file mode 100644
index 0000000..676f55f
--- /dev/null
+++ b/results/rdd/rdd_sharp_coverage.csv
@@ -0,0 +1,27 @@
+Method,fs specification,Learner g,level,Coverage,CI Length,Bias,repetition
+rdflex,cutoff,Global linear,0.9,0.85,2.6390153450770284,0.7633194412256956,100
+rdflex,cutoff,Global linear,0.95,0.91,3.144580737306006,0.7633194412256956,100
+rdflex,cutoff,LGBM,0.9,0.87,0.8654686870010495,0.21670986761632577,100
+rdflex,cutoff,LGBM,0.95,0.91,1.0312695479251124,0.21670986761632577,100
+rdflex,cutoff,Linear,0.9,0.86,2.6623044482444174,0.7653363253149554,100
+rdflex,cutoff,Linear,0.95,0.92,3.1723314153556506,0.7653363253149554,100
+rdflex,cutoff,Stacked,0.9,0.87,0.8292370459653128,0.20641336384869624,100
+rdflex,cutoff,Stacked,0.95,0.94,0.9880968847973659,0.20641336384869624,100
+rdflex,cutoff and score,Global linear,0.9,0.85,2.6339788851766817,0.7619134582859678,100
+rdflex,cutoff and score,Global linear,0.95,0.9,3.1385794251816224,0.7619134582859678,100
+rdflex,cutoff and score,LGBM,0.9,0.87,0.9000347024928754,0.22715287972766593,100
+rdflex,cutoff and score,LGBM,0.95,0.93,1.0724574958026356,0.22715287972766593,100
+rdflex,cutoff and score,Linear,0.9,0.84,2.657278908570506,0.7551838991156445,100
+rdflex,cutoff and score,Linear,0.95,0.94,3.166343115483644,0.7551838991156445,100
+rdflex,cutoff and score,Stacked,0.9,0.87,0.8562989453522138,0.21532588385884185,100
+rdflex,cutoff and score,Stacked,0.95,0.95,1.0203431268230934,0.21532588385884185,100
+rdflex,interacted cutoff and score,Global linear,0.9,0.84,2.645057019999056,0.7772054596119895,100
+rdflex,interacted cutoff and score,Global linear,0.95,0.91,3.151779837006701,0.7772054596119895,100
+rdflex,interacted cutoff and score,LGBM,0.9,0.84,0.9109719935611333,0.23922051107289302,100
+rdflex,interacted cutoff and score,LGBM,0.95,0.95,1.085490081943414,0.23922051107289302,100
+rdflex,interacted cutoff and score,Linear,0.9,0.85,2.6813008747574365,0.7549882284589517,100
+rdflex,interacted cutoff and score,Linear,0.95,0.93,3.194967053682621,0.7549882284589517,100
+rdflex,interacted cutoff and score,Stacked,0.9,0.85,0.8714225944335549,0.21781376289979562,100
+rdflex,interacted cutoff and score,Stacked,0.95,0.96,1.0383640662115956,0.21781376289979562,100
+rdrobust,interacted cutoff and score,linear,0.9,0.85,3.0725067174655942,0.7569969307893883,100
+rdrobust,interacted cutoff and score,linear,0.95,0.93,3.661117566826274,0.7569969307893883,100
diff --git a/results/rdd/rdd_sharp_coverage_metadata.csv b/results/rdd/rdd_sharp_coverage_metadata.csv
new file mode 100644
index 0000000..346ebc1
--- /dev/null
+++ b/results/rdd/rdd_sharp_coverage_metadata.csv
@@ -0,0 +1,2 @@
+DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
+0.9.dev0,rdd_sharp_coverage.py,2024-10-09 15:07:49,406.35497069358826,3.12.4
diff --git a/scripts/rdd/rdd_fuzzy_coverage.py b/scripts/rdd/rdd_fuzzy_coverage.py
index a7ef02e..b0da4ed 100644
--- a/scripts/rdd/rdd_fuzzy_coverage.py
+++ b/scripts/rdd/rdd_fuzzy_coverage.py
@@ -74,6 +74,7 @@
         print("Maximum runtime exceeded. Stopping the simulation.")
         break
 
+    data = datasets[i_rep]
     # get oracle value
     cutoff = 0
     score = data["score"]
diff --git a/scripts/rdd/rdd_sharp_coverage.py b/scripts/rdd/rdd_sharp_coverage.py
index 9c8dc80..969b45f 100644
--- a/scripts/rdd/rdd_sharp_coverage.py
+++ b/scripts/rdd/rdd_sharp_coverage.py
@@ -64,6 +64,7 @@
         print("Maximum runtime exceeded. Stopping the simulation.")
         break
 
+    data = datasets[i_rep]
     # get oracle value
     score = data["score"]
     ite = data["oracle_values"]['Y1'] - data["oracle_values"]['Y0']

From e68936a07645b3454b7927d922162a595c185c7f Mon Sep 17 00:00:00 2001
From: Sven Klaassen <47529404+SvenKlaassen@users.noreply.github.com>
Date: Thu, 10 Oct 2024 18:33:38 +0200
Subject: [PATCH 05/58] update sim

---
 results/rdd/rdd_fuzzy_coverage.csv          | 4 ++--
 results/rdd/rdd_fuzzy_coverage_metadata.csv | 2 +-
 scripts/rdd/rdd_fuzzy_coverage.py           | 8 +++-----
 scripts/rdd/rdd_sharp_coverage.py           | 8 +++-----
 4 files changed, 9 insertions(+), 13 deletions(-)

diff --git a/results/rdd/rdd_fuzzy_coverage.csv b/results/rdd/rdd_fuzzy_coverage.csv
index 10a864c..5ff6190 100644
--- a/results/rdd/rdd_fuzzy_coverage.csv
+++ b/results/rdd/rdd_fuzzy_coverage.csv
@@ -95,5 +95,5 @@ rdflex,interacted cutoff and score,Stacked,Linear,0.9,0.99,85.29228313835699,3.1
 rdflex,interacted cutoff and score,Stacked,Linear,0.95,1.0,101.63202389029637,3.155082488308933,100
 rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.98,23.815976412169956,2.214781308607141,100
 rdflex,interacted cutoff and score,Stacked,Stacked,0.95,0.99,28.378486243193066,2.214781308607141,100
-rdrobust,interacted cutoff and score,linear,linear,0.9,0.99,188.44638549344222,8.674372870881726,100
-rdrobust,interacted cutoff and score,linear,linear,0.95,1.0,224.54771812640732,8.674372870881726,100
+rdrobust,cutoff,linear,linear,0.9,0.99,188.44638549344222,8.674372870881726,100
+rdrobust,cutoff,linear,linear,0.95,1.0,224.54771812640732,8.674372870881726,100
diff --git a/results/rdd/rdd_fuzzy_coverage_metadata.csv b/results/rdd/rdd_fuzzy_coverage_metadata.csv
index 56698e5..de42e72 100644
--- a/results/rdd/rdd_fuzzy_coverage_metadata.csv
+++ b/results/rdd/rdd_fuzzy_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_fuzzy_coverage.py,2024-10-09 17:19:09,7052.292869091034,3.12.4
+0.9.dev0,rdd_fuzzy_coverage.py,2024-10-10 18:14:52,5937.969740152359,3.12.4
diff --git a/scripts/rdd/rdd_fuzzy_coverage.py b/scripts/rdd/rdd_fuzzy_coverage.py
index b0da4ed..2233c9f 100644
--- a/scripts/rdd/rdd_fuzzy_coverage.py
+++ b/scripts/rdd/rdd_fuzzy_coverage.py
@@ -23,14 +23,14 @@
 
 # DGP pars
 n_obs = 500
-fuzzy = True
+cutoff = 0
 
 # to get the best possible comparison between different learners (and settings) we first simulate all datasets
 np.random.seed(42)
 
 datasets = []
 for i in range(n_rep):
-    data = make_simple_rdd_data(n_obs=n_obs, fuzzy=fuzzy)
+    data = make_simple_rdd_data(n_obs=n_obs, fuzzy=True, cutoff=cutoff)
     datasets.append(data)
 
 # set up hyperparameters
@@ -76,13 +76,11 @@
 
     data = datasets[i_rep]
     # get oracle value
-    cutoff = 0
     score = data["score"]
     complier_mask = (((data["D"] == 0) & (data["score"] < cutoff)) | ((data["D"] == 1) & (data["score"] > cutoff)))
 
     ite = data["oracle_values"]['Y1'] - data["oracle_values"]['Y0']
     kernel_reg = KernelReg(endog=ite[complier_mask], exog=score[complier_mask], var_type='c', reg_type='ll')
-
     effect_at_cutoff, _ = kernel_reg.fit(np.array([cutoff]))
     oracle_effect = effect_at_cutoff[0]
 
@@ -109,7 +107,7 @@
                     "Learner g": "linear",
                     "Learner m": "linear",
                     "Method": "rdrobust",
-                    "fs specification": "interacted cutoff and score",
+                    "fs specification": "cutoff",
                     "level": level,
                     "repetition": i_rep}, index=[0])),
             ignore_index=True)
diff --git a/scripts/rdd/rdd_sharp_coverage.py b/scripts/rdd/rdd_sharp_coverage.py
index 969b45f..03a2f08 100644
--- a/scripts/rdd/rdd_sharp_coverage.py
+++ b/scripts/rdd/rdd_sharp_coverage.py
@@ -23,14 +23,14 @@
 
 # DGP pars
 n_obs = 500
-fuzzy = False
+cutoff = 0
 
 # to get the best possible comparison between different learners (and settings) we first simulate all datasets
 np.random.seed(42)
 
 datasets = []
 for i in range(n_rep):
-    data = make_simple_rdd_data(n_obs=n_obs, fuzzy=fuzzy)
+    data = make_simple_rdd_data(n_obs=n_obs, fuzzy=False, cutoff=cutoff)
     datasets.append(data)
 
 # set up hyperparameters
@@ -70,8 +70,6 @@
     ite = data["oracle_values"]['Y1'] - data["oracle_values"]['Y0']
 
     kernel_reg = KernelReg(endog=ite, exog=score, var_type='c', reg_type='ll')
-    cutoff = 0
-
     effect_at_cutoff, _ = kernel_reg.fit(np.array([cutoff]))
     oracle_effect = effect_at_cutoff[0]
 
@@ -97,7 +95,7 @@
                     "Bias": abs(coef - oracle_effect),
                     "Learner g": "linear",
                     "Method": "rdrobust",
-                    "fs specification": "interacted cutoff and score",
+                    "fs specification": "cutoff",
                     "level": level,
                     "repetition": i_rep}, index=[0])),
             ignore_index=True)

From c8bc84d1a5e650e910015178557a7ba3c385e9ce Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Klaa=C3=9Fen?=
 <47529404+SvenKlaassen@users.noreply.github.com>
Date: Mon, 14 Oct 2024 09:28:13 +0200
Subject: [PATCH 06/58] update workflow to use fork

---
 .github/workflows/rdd_sim.yml | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/.github/workflows/rdd_sim.yml b/.github/workflows/rdd_sim.yml
index 3d78822..2cc3321 100644
--- a/.github/workflows/rdd_sim.yml
+++ b/.github/workflows/rdd_sim.yml
@@ -58,6 +58,11 @@ jobs:
         python -m pip install --upgrade pip
         pip install -r requirements.txt
 
+    - name: Install RDFlex from main branch
+      run: |
+        pip uninstall doubleml
+        pip install git+https://github.com/DoubleML/doubleml-rdflex.git@main
+
     - name: Install DoubleML from correct branch
       run: |
         pip install git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}

From bfcf2fc0d1ee6ca3518f86a8342f9ebc64e1776f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Klaa=C3=9Fen?=
 <47529404+SvenKlaassen@users.noreply.github.com>
Date: Mon, 14 Oct 2024 09:29:12 +0200
Subject: [PATCH 07/58] update rdd sim

---
 scripts/rdd/rdd_fuzzy_coverage.py | 4 ++--
 scripts/rdd/rdd_sharp_coverage.py | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/scripts/rdd/rdd_fuzzy_coverage.py b/scripts/rdd/rdd_fuzzy_coverage.py
index 2233c9f..5c6f681 100644
--- a/scripts/rdd/rdd_fuzzy_coverage.py
+++ b/scripts/rdd/rdd_fuzzy_coverage.py
@@ -18,11 +18,11 @@
 
 
 # Number of repetitions
-n_rep = 100
+n_rep = 5
 max_runtime = 5.5 * 3600  # 5.5 hours in seconds
 
 # DGP pars
-n_obs = 500
+n_obs = 2000
 cutoff = 0
 
 # to get the best possible comparison between different learners (and settings) we first simulate all datasets
diff --git a/scripts/rdd/rdd_sharp_coverage.py b/scripts/rdd/rdd_sharp_coverage.py
index 03a2f08..104763e 100644
--- a/scripts/rdd/rdd_sharp_coverage.py
+++ b/scripts/rdd/rdd_sharp_coverage.py
@@ -18,11 +18,11 @@
 
 
 # Number of repetitions
-n_rep = 100
+n_rep = 5
 max_runtime = 5.5 * 3600  # 5.5 hours in seconds
 
 # DGP pars
-n_obs = 500
+n_obs = 1000
 cutoff = 0
 
 # to get the best possible comparison between different learners (and settings) we first simulate all datasets

From 1f6bf331f1c859d1881f33ed3b3bf8342ea0b34c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Klaa=C3=9Fen?=
 <47529404+SvenKlaassen@users.noreply.github.com>
Date: Mon, 14 Oct 2024 09:32:34 +0200
Subject: [PATCH 08/58] Update rdd_sim.yml

---
 .github/workflows/rdd_sim.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/rdd_sim.yml b/.github/workflows/rdd_sim.yml
index 2cc3321..30ec526 100644
--- a/.github/workflows/rdd_sim.yml
+++ b/.github/workflows/rdd_sim.yml
@@ -60,7 +60,7 @@ jobs:
 
     - name: Install RDFlex from main branch
       run: |
-        pip uninstall doubleml
+        pip uninstall -y doubleml
         pip install git+https://github.com/DoubleML/doubleml-rdflex.git@main
 
     - name: Install DoubleML from correct branch

From 241617a2b75ab572b685de542f08d05b295f8930 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Klaa=C3=9Fen?=
 <47529404+SvenKlaassen@users.noreply.github.com>
Date: Mon, 14 Oct 2024 09:34:18 +0200
Subject: [PATCH 09/58] change run name

---
 .github/workflows/rdd_sim.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/rdd_sim.yml b/.github/workflows/rdd_sim.yml
index 30ec526..d9ae74e 100644
--- a/.github/workflows/rdd_sim.yml
+++ b/.github/workflows/rdd_sim.yml
@@ -12,7 +12,7 @@ on:
     types: [run-rdd-scripts]
 
 jobs:
-  run-apo-scripts:
+  run-rdd-scripts:
     runs-on: ubuntu-latest
     strategy:
       matrix:

From e3fa7a90ecc6e2dff4ebbeaa4ee53f38a50675a6 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Klaa=C3=9Fen?=
 <47529404+SvenKlaassen@users.noreply.github.com>
Date: Mon, 14 Oct 2024 09:35:00 +0200
Subject: [PATCH 10/58] add rdrobust

---
 .github/workflows/rdd_sim.yml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.github/workflows/rdd_sim.yml b/.github/workflows/rdd_sim.yml
index d9ae74e..a09afc5 100644
--- a/.github/workflows/rdd_sim.yml
+++ b/.github/workflows/rdd_sim.yml
@@ -62,6 +62,7 @@ jobs:
       run: |
         pip uninstall -y doubleml
         pip install git+https://github.com/DoubleML/doubleml-rdflex.git@main
+        pip install rdrobust
 
     - name: Install DoubleML from correct branch
       run: |

From c4bdbc716bb2d10889803271d571d9c177629e82 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Klaa=C3=9Fen?=
 <47529404+SvenKlaassen@users.noreply.github.com>
Date: Mon, 14 Oct 2024 09:39:29 +0200
Subject: [PATCH 11/58] Update rdd_sim.yml

---
 .github/workflows/rdd_sim.yml | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/rdd_sim.yml b/.github/workflows/rdd_sim.yml
index a09afc5..ba52e05 100644
--- a/.github/workflows/rdd_sim.yml
+++ b/.github/workflows/rdd_sim.yml
@@ -58,16 +58,16 @@ jobs:
         python -m pip install --upgrade pip
         pip install -r requirements.txt
 
+    - name: Install DoubleML from correct branch
+      run: |
+        pip install git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}
+
     - name: Install RDFlex from main branch
       run: |
         pip uninstall -y doubleml
         pip install git+https://github.com/DoubleML/doubleml-rdflex.git@main
         pip install rdrobust
 
-    - name: Install DoubleML from correct branch
-      run: |
-        pip install git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}
-
     - name: Set up Git configuration
       run: |
         git config --global user.name 'github-actions'

From b43a5bc0468d6c2eb420b86b59bae555b4619b8c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Klaa=C3=9Fen?=
 <47529404+SvenKlaassen@users.noreply.github.com>
Date: Mon, 14 Oct 2024 10:17:38 +0200
Subject: [PATCH 12/58] Update rdd_sim.yml

---
 .github/workflows/rdd_sim.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/rdd_sim.yml b/.github/workflows/rdd_sim.yml
index ba52e05..13b64ee 100644
--- a/.github/workflows/rdd_sim.yml
+++ b/.github/workflows/rdd_sim.yml
@@ -78,7 +78,7 @@ jobs:
 
     - name: Commit any existing changes
       run: |
-        git add results/irm
+        git add results/rdd
         git commit -m "Update results from script: ${{ matrix.script }}" || echo "No changed results to commit"
 
     - name: Wait random time

From bc9496b505f7935a0c1ce5ec6f6580672102b21b Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Mon, 14 Oct 2024 08:19:46 +0000
Subject: [PATCH 13/58] Update results from script:
 scripts/rdd/rdd_sharp_coverage.py

---
 results/rdd/rdd_sharp_coverage.csv          | 52 ++++++++++-----------
 results/rdd/rdd_sharp_coverage_metadata.csv |  2 +-
 2 files changed, 27 insertions(+), 27 deletions(-)

diff --git a/results/rdd/rdd_sharp_coverage.csv b/results/rdd/rdd_sharp_coverage.csv
index 676f55f..8c9e04a 100644
--- a/results/rdd/rdd_sharp_coverage.csv
+++ b/results/rdd/rdd_sharp_coverage.csv
@@ -1,27 +1,27 @@
 Method,fs specification,Learner g,level,Coverage,CI Length,Bias,repetition
-rdflex,cutoff,Global linear,0.9,0.85,2.6390153450770284,0.7633194412256956,100
-rdflex,cutoff,Global linear,0.95,0.91,3.144580737306006,0.7633194412256956,100
-rdflex,cutoff,LGBM,0.9,0.87,0.8654686870010495,0.21670986761632577,100
-rdflex,cutoff,LGBM,0.95,0.91,1.0312695479251124,0.21670986761632577,100
-rdflex,cutoff,Linear,0.9,0.86,2.6623044482444174,0.7653363253149554,100
-rdflex,cutoff,Linear,0.95,0.92,3.1723314153556506,0.7653363253149554,100
-rdflex,cutoff,Stacked,0.9,0.87,0.8292370459653128,0.20641336384869624,100
-rdflex,cutoff,Stacked,0.95,0.94,0.9880968847973659,0.20641336384869624,100
-rdflex,cutoff and score,Global linear,0.9,0.85,2.6339788851766817,0.7619134582859678,100
-rdflex,cutoff and score,Global linear,0.95,0.9,3.1385794251816224,0.7619134582859678,100
-rdflex,cutoff and score,LGBM,0.9,0.87,0.9000347024928754,0.22715287972766593,100
-rdflex,cutoff and score,LGBM,0.95,0.93,1.0724574958026356,0.22715287972766593,100
-rdflex,cutoff and score,Linear,0.9,0.84,2.657278908570506,0.7551838991156445,100
-rdflex,cutoff and score,Linear,0.95,0.94,3.166343115483644,0.7551838991156445,100
-rdflex,cutoff and score,Stacked,0.9,0.87,0.8562989453522138,0.21532588385884185,100
-rdflex,cutoff and score,Stacked,0.95,0.95,1.0203431268230934,0.21532588385884185,100
-rdflex,interacted cutoff and score,Global linear,0.9,0.84,2.645057019999056,0.7772054596119895,100
-rdflex,interacted cutoff and score,Global linear,0.95,0.91,3.151779837006701,0.7772054596119895,100
-rdflex,interacted cutoff and score,LGBM,0.9,0.84,0.9109719935611333,0.23922051107289302,100
-rdflex,interacted cutoff and score,LGBM,0.95,0.95,1.085490081943414,0.23922051107289302,100
-rdflex,interacted cutoff and score,Linear,0.9,0.85,2.6813008747574365,0.7549882284589517,100
-rdflex,interacted cutoff and score,Linear,0.95,0.93,3.194967053682621,0.7549882284589517,100
-rdflex,interacted cutoff and score,Stacked,0.9,0.85,0.8714225944335549,0.21781376289979562,100
-rdflex,interacted cutoff and score,Stacked,0.95,0.96,1.0383640662115956,0.21781376289979562,100
-rdrobust,interacted cutoff and score,linear,0.9,0.85,3.0725067174655942,0.7569969307893883,100
-rdrobust,interacted cutoff and score,linear,0.95,0.93,3.661117566826274,0.7569969307893883,100
+rdflex,cutoff,Global linear,0.9,0.8,1.8743273521388104,0.6775368680607832,5
+rdflex,cutoff,Global linear,0.95,0.8,2.233398793203849,0.6775368680607832,5
+rdflex,cutoff,LGBM,0.9,0.8,0.44015753289244053,0.10965985371400153,5
+rdflex,cutoff,LGBM,0.95,0.8,0.524480049688117,0.10965985371400153,5
+rdflex,cutoff,Linear,0.9,0.8,1.8651015770170845,0.7027896715892041,5
+rdflex,cutoff,Linear,0.95,0.8,2.2224056041007176,0.7027896715892041,5
+rdflex,cutoff,Stacked,0.9,0.8,0.42886442921994306,0.10853983203406639,5
+rdflex,cutoff,Stacked,0.95,1.0,0.5110234866790456,0.10853983203406639,5
+rdflex,cutoff and score,Global linear,0.9,0.8,1.872657216741662,0.6682217663676083,5
+rdflex,cutoff and score,Global linear,0.95,0.8,2.231408704132043,0.6682217663676083,5
+rdflex,cutoff and score,LGBM,0.9,0.8,0.43870640194989985,0.11595087523066612,5
+rdflex,cutoff and score,LGBM,0.95,0.8,0.5227509205196433,0.11595087523066612,5
+rdflex,cutoff and score,Linear,0.9,0.8,1.87199076730234,0.6942204584187508,5
+rdflex,cutoff and score,Linear,0.95,0.8,2.2306145806445876,0.6942204584187508,5
+rdflex,cutoff and score,Stacked,0.9,1.0,0.4375651464674375,0.10814551871963884,5
+rdflex,cutoff and score,Stacked,0.95,1.0,0.5213910307360577,0.10814551871963884,5
+rdflex,interacted cutoff and score,Global linear,0.9,0.8,1.876207477943963,0.6822430434055142,5
+rdflex,interacted cutoff and score,Global linear,0.95,0.8,2.2356391012799746,0.6822430434055142,5
+rdflex,interacted cutoff and score,LGBM,0.9,0.8,0.48409300240369346,0.09666812716019105,5
+rdflex,interacted cutoff and score,LGBM,0.95,1.0,0.5768323906350199,0.09666812716019105,5
+rdflex,interacted cutoff and score,Linear,0.9,0.8,1.8730302319924128,0.690953060104218,5
+rdflex,interacted cutoff and score,Linear,0.95,0.8,2.2318531792179575,0.690953060104218,5
+rdflex,interacted cutoff and score,Stacked,0.9,1.0,0.45440276301542604,0.09720984628369075,5
+rdflex,interacted cutoff and score,Stacked,0.95,1.0,0.541454288328599,0.09720984628369075,5
+rdrobust,cutoff,linear,0.9,0.8,2.161630254948009,0.6687746075451069,5
+rdrobust,cutoff,linear,0.95,0.8,2.575741317142273,0.6687746075451069,5
diff --git a/results/rdd/rdd_sharp_coverage_metadata.csv b/results/rdd/rdd_sharp_coverage_metadata.csv
index 346ebc1..d0338f8 100644
--- a/results/rdd/rdd_sharp_coverage_metadata.csv
+++ b/results/rdd/rdd_sharp_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_sharp_coverage.py,2024-10-09 15:07:49,406.35497069358826,3.12.4
+0.9.dev0,rdd_sharp_coverage.py,2024-10-14 08:19:46,41.72558879852295,3.12.7

From 78ce92a732e75b464ef9fe3dc4d2a487fa6e749e Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Mon, 14 Oct 2024 08:24:15 +0000
Subject: [PATCH 14/58] Update results from script:
 scripts/rdd/rdd_fuzzy_coverage.py

---
 results/rdd/rdd_fuzzy_coverage.csv          | 196 ++++++++++----------
 results/rdd/rdd_fuzzy_coverage_metadata.csv |   2 +-
 2 files changed, 99 insertions(+), 99 deletions(-)

diff --git a/results/rdd/rdd_fuzzy_coverage.csv b/results/rdd/rdd_fuzzy_coverage.csv
index 5ff6190..e66dd5f 100644
--- a/results/rdd/rdd_fuzzy_coverage.csv
+++ b/results/rdd/rdd_fuzzy_coverage.csv
@@ -1,99 +1,99 @@
 Method,fs specification,Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-rdflex,cutoff,Global linear,Global linear,0.9,1.0,24576.052985663362,33.714993058400886,100
-rdflex,cutoff,Global linear,Global linear,0.95,1.0,29284.173342111826,33.714993058400886,100
-rdflex,cutoff,Global linear,LGBM,0.9,1.0,212.7670843346672,7.394068380531208,100
-rdflex,cutoff,Global linear,LGBM,0.95,1.0,253.52761823824412,7.394068380531208,100
-rdflex,cutoff,Global linear,Linear,0.9,1.0,7285.560991813301,25.24811183810531,100
-rdflex,cutoff,Global linear,Linear,0.95,1.0,8681.281371880557,25.24811183810531,100
-rdflex,cutoff,Global linear,Stacked,0.9,1.0,394.455579919443,9.344964372631935,100
-rdflex,cutoff,Global linear,Stacked,0.95,1.0,470.02281386936954,9.344964372631935,100
-rdflex,cutoff,LGBM,Global linear,0.9,0.99,72.60636323582686,2.7988886732167635,100
-rdflex,cutoff,LGBM,Global linear,0.95,1.0,86.51581797852712,2.7988886732167635,100
-rdflex,cutoff,LGBM,LGBM,0.9,0.99,96.8467863259473,3.616213865899996,100
-rdflex,cutoff,LGBM,LGBM,0.95,1.0,115.40006363308038,3.616213865899996,100
-rdflex,cutoff,LGBM,Linear,0.9,1.0,502.9674323275353,4.744361836099421,100
-rdflex,cutoff,LGBM,Linear,0.95,1.0,599.3226610598828,4.744361836099421,100
-rdflex,cutoff,LGBM,Stacked,0.9,0.97,30.402335642968584,2.136680518057323,100
-rdflex,cutoff,LGBM,Stacked,0.95,1.0,36.22661732919947,2.136680518057323,100
-rdflex,cutoff,Linear,Global linear,0.9,1.0,288.2129055526289,6.8505494565519385,100
-rdflex,cutoff,Linear,Global linear,0.95,1.0,343.42685908760353,6.8505494565519385,100
-rdflex,cutoff,Linear,LGBM,0.9,1.0,1267.7114353254287,11.7553962645311,100
-rdflex,cutoff,Linear,LGBM,0.95,1.0,1510.571345264586,11.7553962645311,100
-rdflex,cutoff,Linear,Linear,0.9,1.0,450781.6204890172,106.12716308132217,100
-rdflex,cutoff,Linear,Linear,0.95,1.0,537139.4308735916,106.12716308132217,100
-rdflex,cutoff,Linear,Stacked,0.9,1.0,881.7068963348019,9.734537855926657,100
-rdflex,cutoff,Linear,Stacked,0.95,1.0,1050.6185677686365,9.734537855926657,100
-rdflex,cutoff,Stacked,Global linear,0.9,0.97,1290.6705810610117,5.997544912636781,100
-rdflex,cutoff,Stacked,Global linear,0.95,1.0,1537.92885478411,5.997544912636781,100
-rdflex,cutoff,Stacked,LGBM,0.9,1.0,136.62140422287027,3.333628982473081,100
-rdflex,cutoff,Stacked,LGBM,0.95,1.0,162.7944440809591,3.333628982473081,100
-rdflex,cutoff,Stacked,Linear,0.9,0.97,1428.1853101775168,6.810519084378244,100
-rdflex,cutoff,Stacked,Linear,0.95,1.0,1701.7877611304823,6.810519084378244,100
-rdflex,cutoff,Stacked,Stacked,0.9,0.97,31.755052523109708,2.457304897883856,100
-rdflex,cutoff,Stacked,Stacked,0.95,1.0,37.838478909411805,2.457304897883856,100
-rdflex,cutoff and score,Global linear,Global linear,0.9,1.0,360.03334552320234,9.290898235230898,100
-rdflex,cutoff and score,Global linear,Global linear,0.95,1.0,429.00619173438497,9.290898235230898,100
-rdflex,cutoff and score,Global linear,LGBM,0.9,1.0,65.141857558003,5.866315242081892,100
-rdflex,cutoff and score,Global linear,LGBM,0.95,1.0,77.62131086177858,5.866315242081892,100
-rdflex,cutoff and score,Global linear,Linear,0.9,1.0,188.2737747038422,7.579674700252163,100
-rdflex,cutoff and score,Global linear,Linear,0.95,1.0,224.3420396846204,7.579674700252163,100
-rdflex,cutoff and score,Global linear,Stacked,0.9,1.0,101.09651866526238,6.189455751901226,100
-rdflex,cutoff and score,Global linear,Stacked,0.95,1.0,120.46393204818669,6.189455751901226,100
-rdflex,cutoff and score,LGBM,Global linear,0.9,0.97,73.65691077194248,3.3577859423993432,100
-rdflex,cutoff and score,LGBM,Global linear,0.95,1.0,87.76762257748713,3.3577859423993432,100
-rdflex,cutoff and score,LGBM,LGBM,0.9,0.98,906.6323063282008,6.052558120730604,100
-rdflex,cutoff and score,LGBM,LGBM,0.95,1.0,1080.3190256613543,6.052558120730604,100
-rdflex,cutoff and score,LGBM,Linear,0.9,0.97,704.8526691961484,5.409173897890411,100
-rdflex,cutoff and score,LGBM,Linear,0.95,0.99,839.8837582841852,5.409173897890411,100
-rdflex,cutoff and score,LGBM,Stacked,0.9,0.99,209.1865557589259,3.8332926812316845,100
-rdflex,cutoff and score,LGBM,Stacked,0.95,1.0,249.26115529036716,3.8332926812316845,100
-rdflex,cutoff and score,Linear,Global linear,0.9,0.99,3016.5600996185135,14.768373929828062,100
-rdflex,cutoff and score,Linear,Global linear,0.95,1.0,3594.4530598814645,14.768373929828062,100
-rdflex,cutoff and score,Linear,LGBM,0.9,1.0,13407.437191137702,29.954023874117556,100
-rdflex,cutoff and score,Linear,LGBM,0.95,1.0,15975.94678884338,29.954023874117556,100
-rdflex,cutoff and score,Linear,Linear,0.9,1.0,159.9589119416921,7.375932003888324,100
-rdflex,cutoff and score,Linear,Linear,0.95,1.0,190.60279971111376,7.375932003888324,100
-rdflex,cutoff and score,Linear,Stacked,0.9,1.0,77.8159882626384,6.6020932037079305,100
-rdflex,cutoff and score,Linear,Stacked,0.95,1.0,92.72346907781267,6.6020932037079305,100
-rdflex,cutoff and score,Stacked,Global linear,0.9,0.99,296.00629012356245,4.83669396654298,100
-rdflex,cutoff and score,Stacked,Global linear,0.95,1.0,352.7132495763485,4.83669396654298,100
-rdflex,cutoff and score,Stacked,LGBM,0.9,0.99,653.7024865250983,5.333034986632671,100
-rdflex,cutoff and score,Stacked,LGBM,0.95,1.0,778.934556364189,5.333034986632671,100
-rdflex,cutoff and score,Stacked,Linear,0.9,0.96,260.69680825739044,4.667422911300441,100
-rdflex,cutoff and score,Stacked,Linear,0.95,1.0,310.6394068729521,4.667422911300441,100
-rdflex,cutoff and score,Stacked,Stacked,0.9,0.98,1028.1581452399262,6.541291874878417,100
-rdflex,cutoff and score,Stacked,Stacked,0.95,1.0,1225.125994230008,6.541291874878417,100
-rdflex,interacted cutoff and score,Global linear,Global linear,0.9,1.0,115.02137421624799,6.955730839588052,100
-rdflex,interacted cutoff and score,Global linear,Global linear,0.95,1.0,137.05642084029714,6.955730839588052,100
-rdflex,interacted cutoff and score,Global linear,LGBM,0.9,1.0,2138.206925338846,13.383695980176464,100
-rdflex,interacted cutoff and score,Global linear,LGBM,0.95,1.0,2547.830698422324,13.383695980176464,100
-rdflex,interacted cutoff and score,Global linear,Linear,0.9,1.0,248.64260039669713,8.933890175218044,100
-rdflex,interacted cutoff and score,Global linear,Linear,0.95,1.0,296.27593228651983,8.933890175218044,100
-rdflex,interacted cutoff and score,Global linear,Stacked,0.9,1.0,7830.074178774233,26.977813963864392,100
-rdflex,interacted cutoff and score,Global linear,Stacked,0.95,1.0,9330.108852978992,26.977813963864392,100
-rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.96,110.87219823076155,3.26608101071588,100
-rdflex,interacted cutoff and score,LGBM,Global linear,0.95,1.0,132.11237271113686,3.26608101071588,100
-rdflex,interacted cutoff and score,LGBM,LGBM,0.9,1.0,20.922562677679036,1.9592975523809535,100
-rdflex,interacted cutoff and score,LGBM,LGBM,0.95,1.0,24.93077112796655,1.9592975523809535,100
-rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.98,93.57449880755165,3.3828798935653133,100
-rdflex,interacted cutoff and score,LGBM,Linear,0.95,1.0,111.50089255911544,3.3828798935653133,100
-rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.98,28.741965545451134,2.508094158883194,100
-rdflex,interacted cutoff and score,LGBM,Stacked,0.95,1.0,34.24816432960168,2.508094158883194,100
-rdflex,interacted cutoff and score,Linear,Global linear,0.9,1.0,20640.141712201705,18.641835328086387,100
-rdflex,interacted cutoff and score,Linear,Global linear,0.95,1.0,24594.245791155576,18.641835328086387,100
-rdflex,interacted cutoff and score,Linear,LGBM,0.9,1.0,298.98997131061145,9.730810172540227,100
-rdflex,interacted cutoff and score,Linear,LGBM,0.95,1.0,356.2685249954775,9.730810172540227,100
-rdflex,interacted cutoff and score,Linear,Linear,0.9,1.0,5006.456402704061,18.416688138138774,100
-rdflex,interacted cutoff and score,Linear,Linear,0.95,1.0,5965.560751843976,18.416688138138774,100
-rdflex,interacted cutoff and score,Linear,Stacked,0.9,1.0,275.5207382066559,10.066409170458378,100
-rdflex,interacted cutoff and score,Linear,Stacked,0.95,1.0,328.30320888781813,10.066409170458378,100
-rdflex,interacted cutoff and score,Stacked,Global linear,0.9,0.97,867.4679612121456,5.903459537041831,100
-rdflex,interacted cutoff and score,Stacked,Global linear,0.95,1.0,1033.6518300836956,5.903459537041831,100
-rdflex,interacted cutoff and score,Stacked,LGBM,0.9,0.97,263.20550887930045,4.132180855975779,100
-rdflex,interacted cutoff and score,Stacked,LGBM,0.95,1.0,313.6287080401628,4.132180855975779,100
-rdflex,interacted cutoff and score,Stacked,Linear,0.9,0.99,85.29228313835699,3.155082488308933,100
-rdflex,interacted cutoff and score,Stacked,Linear,0.95,1.0,101.63202389029637,3.155082488308933,100
-rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.98,23.815976412169956,2.214781308607141,100
-rdflex,interacted cutoff and score,Stacked,Stacked,0.95,0.99,28.378486243193066,2.214781308607141,100
-rdrobust,cutoff,linear,linear,0.9,0.99,188.44638549344222,8.674372870881726,100
-rdrobust,cutoff,linear,linear,0.95,1.0,224.54771812640732,8.674372870881726,100
+rdflex,cutoff,Global linear,Global linear,0.9,0.8,14.423037908091597,3.2637402601909544,5
+rdflex,cutoff,Global linear,Global linear,0.95,1.0,17.186109684366134,3.2637402601909544,5
+rdflex,cutoff,Global linear,LGBM,0.9,1.0,9.60760402812852,2.610897383935538,5
+rdflex,cutoff,Global linear,LGBM,0.95,1.0,11.448166307511448,2.610897383935538,5
+rdflex,cutoff,Global linear,Linear,0.9,1.0,14.226538661834956,3.3206952967859835,5
+rdflex,cutoff,Global linear,Linear,0.95,1.0,16.95196639079777,3.3206952967859835,5
+rdflex,cutoff,Global linear,Stacked,0.9,1.0,11.479292659550719,2.892434062670725,5
+rdflex,cutoff,Global linear,Stacked,0.95,1.0,13.678420871049463,2.892434062670725,5
+rdflex,cutoff,LGBM,Global linear,0.9,1.0,2.291086593513875,0.3217115365585489,5
+rdflex,cutoff,LGBM,Global linear,0.95,1.0,2.729998058898547,0.3217115365585489,5
+rdflex,cutoff,LGBM,LGBM,0.9,1.0,1.8232352455660876,0.471335656388427,5
+rdflex,cutoff,LGBM,LGBM,0.95,1.0,2.172518793223295,0.471335656388427,5
+rdflex,cutoff,LGBM,Linear,0.9,1.0,2.5036910885538886,0.46592543647375206,5
+rdflex,cutoff,LGBM,Linear,0.95,1.0,2.983331940042759,0.46592543647375206,5
+rdflex,cutoff,LGBM,Stacked,0.9,1.0,1.983251590128728,0.3648095017291908,5
+rdflex,cutoff,LGBM,Stacked,0.95,1.0,2.3631900281232623,0.3648095017291908,5
+rdflex,cutoff,Linear,Global linear,0.9,0.8,13.898849040803778,3.2754800847865724,5
+rdflex,cutoff,Linear,Global linear,0.95,1.0,16.56150012388803,3.2754800847865724,5
+rdflex,cutoff,Linear,LGBM,0.9,1.0,8.788094435735177,2.454463244345884,5
+rdflex,cutoff,Linear,LGBM,0.95,1.0,10.471660398561387,2.454463244345884,5
+rdflex,cutoff,Linear,Linear,0.9,0.8,14.47344689140013,3.3491813910739134,5
+rdflex,cutoff,Linear,Linear,0.95,1.0,17.246175692771462,3.3491813910739134,5
+rdflex,cutoff,Linear,Stacked,0.9,1.0,10.558846700439386,2.764041856725428,5
+rdflex,cutoff,Linear,Stacked,0.95,1.0,12.581641862866709,2.764041856725428,5
+rdflex,cutoff,Stacked,Global linear,0.9,0.8,2.4355448606892423,0.3881680057707292,5
+rdflex,cutoff,Stacked,Global linear,0.95,1.0,2.9021307011553152,0.3881680057707292,5
+rdflex,cutoff,Stacked,LGBM,0.9,1.0,1.7612830354582933,0.43067758587432187,5
+rdflex,cutoff,Stacked,LGBM,0.95,1.0,2.09869818172063,0.43067758587432187,5
+rdflex,cutoff,Stacked,Linear,0.9,1.0,2.0422134023298866,0.21267147182739804,5
+rdflex,cutoff,Stacked,Linear,0.95,1.0,2.433447360741768,0.21267147182739804,5
+rdflex,cutoff,Stacked,Stacked,0.9,0.8,2.0563286274932917,0.5572667177929984,5
+rdflex,cutoff,Stacked,Stacked,0.95,0.8,2.4502666889182345,0.5572667177929984,5
+rdflex,cutoff and score,Global linear,Global linear,0.9,1.0,14.259416097319534,3.29291711658142,5
+rdflex,cutoff and score,Global linear,Global linear,0.95,1.0,16.991142271494972,3.29291711658142,5
+rdflex,cutoff and score,Global linear,LGBM,0.9,1.0,11.497486915431436,2.866354293380936,5
+rdflex,cutoff and score,Global linear,LGBM,0.95,1.0,13.70010066411275,2.866354293380936,5
+rdflex,cutoff and score,Global linear,Linear,0.9,1.0,14.322347851500998,3.297628178611928,5
+rdflex,cutoff and score,Global linear,Linear,0.95,1.0,17.066130081752714,3.297628178611928,5
+rdflex,cutoff and score,Global linear,Stacked,0.9,1.0,11.187221250336403,2.8665327874888407,5
+rdflex,cutoff and score,Global linear,Stacked,0.95,1.0,13.33039632126938,2.8665327874888407,5
+rdflex,cutoff and score,LGBM,Global linear,0.9,1.0,2.132646705302484,0.35115271453669183,5
+rdflex,cutoff and score,LGBM,Global linear,0.95,1.0,2.5412052876022835,0.35115271453669183,5
+rdflex,cutoff and score,LGBM,LGBM,0.9,1.0,1.651573825829961,0.49015621894821504,5
+rdflex,cutoff and score,LGBM,LGBM,0.95,1.0,1.9679715954027883,0.49015621894821504,5
+rdflex,cutoff and score,LGBM,Linear,0.9,1.0,2.0653982476186394,0.33633981978688077,5
+rdflex,cutoff and score,LGBM,Linear,0.95,1.0,2.4610738078666157,0.33633981978688077,5
+rdflex,cutoff and score,LGBM,Stacked,0.9,1.0,2.070887518085169,0.48315068117208615,5
+rdflex,cutoff and score,LGBM,Stacked,0.95,1.0,2.4676146770597835,0.48315068117208615,5
+rdflex,cutoff and score,Linear,Global linear,0.9,0.8,13.834500877512358,3.252602683579687,5
+rdflex,cutoff and score,Linear,Global linear,0.95,1.0,16.484824558077207,3.252602683579687,5
+rdflex,cutoff and score,Linear,LGBM,0.9,1.0,11.021494973340559,2.957462426090728,5
+rdflex,cutoff and score,Linear,LGBM,0.95,1.0,13.132921282225468,2.957462426090728,5
+rdflex,cutoff and score,Linear,Linear,0.9,0.8,13.565400587199502,3.273961937011743,5
+rdflex,cutoff and score,Linear,Linear,0.95,1.0,16.16417178472376,3.273961937011743,5
+rdflex,cutoff and score,Linear,Stacked,0.9,1.0,9.781507067833797,2.5759545181110926,5
+rdflex,cutoff and score,Linear,Stacked,0.95,1.0,11.655384560272386,2.5759545181110926,5
+rdflex,cutoff and score,Stacked,Global linear,0.9,0.8,1.9443850931574904,0.35287630976386913,5
+rdflex,cutoff and score,Stacked,Global linear,0.95,1.0,2.3168777405004146,0.35287630976386913,5
+rdflex,cutoff and score,Stacked,LGBM,0.9,1.0,1.5606416431884977,0.27407774182095623,5
+rdflex,cutoff and score,Stacked,LGBM,0.95,1.0,1.8596192167518069,0.27407774182095623,5
+rdflex,cutoff and score,Stacked,Linear,0.9,1.0,2.193836968365324,0.3692120996481659,5
+rdflex,cutoff and score,Stacked,Linear,0.95,1.0,2.614117983201815,0.3692120996481659,5
+rdflex,cutoff and score,Stacked,Stacked,0.9,1.0,1.8666724118484936,0.5368999174526484,5
+rdflex,cutoff and score,Stacked,Stacked,0.95,1.0,2.2242773692503803,0.5368999174526484,5
+rdflex,interacted cutoff and score,Global linear,Global linear,0.9,0.8,11.50038602288641,2.8517535553634956,5
+rdflex,interacted cutoff and score,Global linear,Global linear,0.95,1.0,13.703555163714393,2.8517535553634956,5
+rdflex,interacted cutoff and score,Global linear,LGBM,0.9,1.0,10.315801252711834,2.7007313341878936,5
+rdflex,interacted cutoff and score,Global linear,LGBM,0.95,1.0,12.292035349346543,2.7007313341878936,5
+rdflex,interacted cutoff and score,Global linear,Linear,0.9,0.8,11.729502101422899,2.9285377690970025,5
+rdflex,interacted cutoff and score,Global linear,Linear,0.95,1.0,13.976563810108567,2.9285377690970025,5
+rdflex,interacted cutoff and score,Global linear,Stacked,0.9,1.0,10.084512037249876,2.6635463803766095,5
+rdflex,interacted cutoff and score,Global linear,Stacked,0.95,1.0,12.016437250591622,2.6635463803766095,5
+rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.8,2.4613080577042163,0.6177915730998491,5
+rdflex,interacted cutoff and score,LGBM,Global linear,0.95,0.8,2.932829443857146,0.6177915730998491,5
+rdflex,interacted cutoff and score,LGBM,LGBM,0.9,1.0,1.9380473017675328,0.3240944835816227,5
+rdflex,interacted cutoff and score,LGBM,LGBM,0.95,1.0,2.3093257962651896,0.3240944835816227,5
+rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.8,2.3048779458142628,0.3381467569608999,5
+rdflex,interacted cutoff and score,LGBM,Linear,0.95,1.0,2.7464314687557887,0.3381467569608999,5
+rdflex,interacted cutoff and score,LGBM,Stacked,0.9,1.0,1.9806236593394437,0.34797999285711156,5
+rdflex,interacted cutoff and score,LGBM,Stacked,0.95,1.0,2.36005865544884,0.34797999285711156,5
+rdflex,interacted cutoff and score,Linear,Global linear,0.9,0.8,14.980877656814286,3.4800582831380575,5
+rdflex,interacted cutoff and score,Linear,Global linear,0.95,1.0,17.85081674323539,3.4800582831380575,5
+rdflex,interacted cutoff and score,Linear,LGBM,0.9,1.0,9.140955749697142,2.5395424847293753,5
+rdflex,interacted cutoff and score,Linear,LGBM,0.95,1.0,10.892120587584234,2.5395424847293753,5
+rdflex,interacted cutoff and score,Linear,Linear,0.9,0.8,15.4138192982352,3.6678662653096916,5
+rdflex,interacted cutoff and score,Linear,Linear,0.95,1.0,18.366698527905392,3.6678662653096916,5
+rdflex,interacted cutoff and score,Linear,Stacked,0.9,1.0,10.864595627804398,2.894493634370918,5
+rdflex,interacted cutoff and score,Linear,Stacked,0.95,1.0,12.945964180748467,2.894493634370918,5
+rdflex,interacted cutoff and score,Stacked,Global linear,0.9,1.0,2.421350027458176,0.2543821651969947,5
+rdflex,interacted cutoff and score,Stacked,Global linear,0.95,1.0,2.885216514115459,0.2543821651969947,5
+rdflex,interacted cutoff and score,Stacked,LGBM,0.9,1.0,1.9090916620591405,0.5916268970924577,5
+rdflex,interacted cutoff and score,Stacked,LGBM,0.95,1.0,2.274823023466525,0.5916268970924577,5
+rdflex,interacted cutoff and score,Stacked,Linear,0.9,1.0,2.4287704707086424,0.42238035779134736,5
+rdflex,interacted cutoff and score,Stacked,Linear,0.95,1.0,2.8940585176116564,0.42238035779134736,5
+rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.8,2.3752766407951578,0.5905486473170087,5
+rdflex,interacted cutoff and score,Stacked,Stacked,0.95,1.0,2.830316687756643,0.5905486473170087,5
+rdrobust,cutoff,linear,linear,0.9,1.0,13.247577083256981,2.876321200969484,5
+rdrobust,cutoff,linear,linear,0.95,1.0,15.785461721432487,2.876321200969484,5
diff --git a/results/rdd/rdd_fuzzy_coverage_metadata.csv b/results/rdd/rdd_fuzzy_coverage_metadata.csv
index de42e72..49bcf8c 100644
--- a/results/rdd/rdd_fuzzy_coverage_metadata.csv
+++ b/results/rdd/rdd_fuzzy_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_fuzzy_coverage.py,2024-10-10 18:14:52,5937.969740152359,3.12.4
+0.9.dev0,rdd_fuzzy_coverage.py,2024-10-14 08:24:15,310.4044132232666,3.12.7

From 1483d7075a1835eacd1dafc35d652e82f27af723 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Klaa=C3=9Fen?=
 <47529404+SvenKlaassen@users.noreply.github.com>
Date: Mon, 14 Oct 2024 10:31:31 +0200
Subject: [PATCH 15/58] increase rdd repetitions

---
 scripts/rdd/rdd_fuzzy_coverage.py | 2 +-
 scripts/rdd/rdd_sharp_coverage.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/scripts/rdd/rdd_fuzzy_coverage.py b/scripts/rdd/rdd_fuzzy_coverage.py
index 5c6f681..271afea 100644
--- a/scripts/rdd/rdd_fuzzy_coverage.py
+++ b/scripts/rdd/rdd_fuzzy_coverage.py
@@ -18,7 +18,7 @@
 
 
 # Number of repetitions
-n_rep = 5
+n_rep = 200
 max_runtime = 5.5 * 3600  # 5.5 hours in seconds
 
 # DGP pars
diff --git a/scripts/rdd/rdd_sharp_coverage.py b/scripts/rdd/rdd_sharp_coverage.py
index 104763e..eb528d1 100644
--- a/scripts/rdd/rdd_sharp_coverage.py
+++ b/scripts/rdd/rdd_sharp_coverage.py
@@ -18,7 +18,7 @@
 
 
 # Number of repetitions
-n_rep = 5
+n_rep = 200
 max_runtime = 5.5 * 3600  # 5.5 hours in seconds
 
 # DGP pars

From 4961acea25dace38ca8b2393b9ed44ccea60e582 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Mon, 14 Oct 2024 09:00:23 +0000
Subject: [PATCH 16/58] Update results from script:
 scripts/rdd/rdd_sharp_coverage.py

---
 results/rdd/rdd_sharp_coverage.csv          | 52 ++++++++++-----------
 results/rdd/rdd_sharp_coverage_metadata.csv |  2 +-
 2 files changed, 27 insertions(+), 27 deletions(-)

diff --git a/results/rdd/rdd_sharp_coverage.csv b/results/rdd/rdd_sharp_coverage.csv
index 8c9e04a..d5617c2 100644
--- a/results/rdd/rdd_sharp_coverage.csv
+++ b/results/rdd/rdd_sharp_coverage.csv
@@ -1,27 +1,27 @@
 Method,fs specification,Learner g,level,Coverage,CI Length,Bias,repetition
-rdflex,cutoff,Global linear,0.9,0.8,1.8743273521388104,0.6775368680607832,5
-rdflex,cutoff,Global linear,0.95,0.8,2.233398793203849,0.6775368680607832,5
-rdflex,cutoff,LGBM,0.9,0.8,0.44015753289244053,0.10965985371400153,5
-rdflex,cutoff,LGBM,0.95,0.8,0.524480049688117,0.10965985371400153,5
-rdflex,cutoff,Linear,0.9,0.8,1.8651015770170845,0.7027896715892041,5
-rdflex,cutoff,Linear,0.95,0.8,2.2224056041007176,0.7027896715892041,5
-rdflex,cutoff,Stacked,0.9,0.8,0.42886442921994306,0.10853983203406639,5
-rdflex,cutoff,Stacked,0.95,1.0,0.5110234866790456,0.10853983203406639,5
-rdflex,cutoff and score,Global linear,0.9,0.8,1.872657216741662,0.6682217663676083,5
-rdflex,cutoff and score,Global linear,0.95,0.8,2.231408704132043,0.6682217663676083,5
-rdflex,cutoff and score,LGBM,0.9,0.8,0.43870640194989985,0.11595087523066612,5
-rdflex,cutoff and score,LGBM,0.95,0.8,0.5227509205196433,0.11595087523066612,5
-rdflex,cutoff and score,Linear,0.9,0.8,1.87199076730234,0.6942204584187508,5
-rdflex,cutoff and score,Linear,0.95,0.8,2.2306145806445876,0.6942204584187508,5
-rdflex,cutoff and score,Stacked,0.9,1.0,0.4375651464674375,0.10814551871963884,5
-rdflex,cutoff and score,Stacked,0.95,1.0,0.5213910307360577,0.10814551871963884,5
-rdflex,interacted cutoff and score,Global linear,0.9,0.8,1.876207477943963,0.6822430434055142,5
-rdflex,interacted cutoff and score,Global linear,0.95,0.8,2.2356391012799746,0.6822430434055142,5
-rdflex,interacted cutoff and score,LGBM,0.9,0.8,0.48409300240369346,0.09666812716019105,5
-rdflex,interacted cutoff and score,LGBM,0.95,1.0,0.5768323906350199,0.09666812716019105,5
-rdflex,interacted cutoff and score,Linear,0.9,0.8,1.8730302319924128,0.690953060104218,5
-rdflex,interacted cutoff and score,Linear,0.95,0.8,2.2318531792179575,0.690953060104218,5
-rdflex,interacted cutoff and score,Stacked,0.9,1.0,0.45440276301542604,0.09720984628369075,5
-rdflex,interacted cutoff and score,Stacked,0.95,1.0,0.541454288328599,0.09720984628369075,5
-rdrobust,cutoff,linear,0.9,0.8,2.161630254948009,0.6687746075451069,5
-rdrobust,cutoff,linear,0.95,0.8,2.575741317142273,0.6687746075451069,5
+rdflex,cutoff,Global linear,0.9,0.845,1.866210870042375,0.5038360519795877,200
+rdflex,cutoff,Global linear,0.95,0.885,2.223727408267512,0.5038360519795877,200
+rdflex,cutoff,LGBM,0.9,0.875,0.46812541151643167,0.12861132896027008,200
+rdflex,cutoff,LGBM,0.95,0.92,0.5578058325595114,0.12861132896027008,200
+rdflex,cutoff,Linear,0.9,0.84,1.8736415637299357,0.5135146512043519,200
+rdflex,cutoff,Linear,0.95,0.88,2.23258162591286,0.5135146512043519,200
+rdflex,cutoff,Stacked,0.9,0.865,0.4595500872797082,0.1257126877847947,200
+rdflex,cutoff,Stacked,0.95,0.93,0.5475877034905549,0.1257126877847947,200
+rdflex,cutoff and score,Global linear,0.9,0.85,1.8654996931859682,0.5051156412170476,200
+rdflex,cutoff and score,Global linear,0.95,0.88,2.222879988775372,0.5051156412170476,200
+rdflex,cutoff and score,LGBM,0.9,0.865,0.4800927111671489,0.1267152246127786,200
+rdflex,cutoff and score,LGBM,0.95,0.945,0.5720657496264642,0.1267152246127786,200
+rdflex,cutoff and score,Linear,0.9,0.85,1.8717967972330274,0.5120276627581323,200
+rdflex,cutoff and score,Linear,0.95,0.89,2.2303834510512295,0.5120276627581323,200
+rdflex,cutoff and score,Stacked,0.9,0.84,0.4705945727392839,0.13524794362256828,200
+rdflex,cutoff and score,Stacked,0.95,0.92,0.5607480196268084,0.13524794362256828,200
+rdflex,interacted cutoff and score,Global linear,0.9,0.84,1.8688480818750401,0.5042547628696261,200
+rdflex,interacted cutoff and score,Global linear,0.95,0.895,2.2268698399872306,0.5042547628696261,200
+rdflex,interacted cutoff and score,LGBM,0.9,0.825,0.48245074981985836,0.1364434399455555,200
+rdflex,interacted cutoff and score,LGBM,0.95,0.905,0.574875525984516,0.1364434399455555,200
+rdflex,interacted cutoff and score,Linear,0.9,0.84,1.8808660437088858,0.5104091884554597,200
+rdflex,interacted cutoff and score,Linear,0.95,0.885,2.241190124768783,0.5104091884554597,200
+rdflex,interacted cutoff and score,Stacked,0.9,0.85,0.4797858036570431,0.1377828475018157,200
+rdflex,interacted cutoff and score,Stacked,0.95,0.9,0.5717000467720971,0.1377828475018157,200
+rdrobust,cutoff,linear,0.9,0.84,2.184383574713776,0.5092603596094496,200
+rdrobust,cutoff,linear,0.95,0.895,2.602853569891644,0.5092603596094496,200
diff --git a/results/rdd/rdd_sharp_coverage_metadata.csv b/results/rdd/rdd_sharp_coverage_metadata.csv
index d0338f8..f84517e 100644
--- a/results/rdd/rdd_sharp_coverage_metadata.csv
+++ b/results/rdd/rdd_sharp_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_sharp_coverage.py,2024-10-14 08:19:46,41.72558879852295,3.12.7
+0.9.dev0,rdd_sharp_coverage.py,2024-10-14 09:00:22,1636.632357597351,3.12.7

From eaa1a6ae0904aad62662220033855f49290164f0 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Mon, 14 Oct 2024 11:56:14 +0000
Subject: [PATCH 17/58] Update results from script:
 scripts/rdd/rdd_fuzzy_coverage.py

---
 results/rdd/rdd_fuzzy_coverage.csv          | 196 ++++++++++----------
 results/rdd/rdd_fuzzy_coverage_metadata.csv |   2 +-
 2 files changed, 99 insertions(+), 99 deletions(-)

diff --git a/results/rdd/rdd_fuzzy_coverage.csv b/results/rdd/rdd_fuzzy_coverage.csv
index e66dd5f..f1ce596 100644
--- a/results/rdd/rdd_fuzzy_coverage.csv
+++ b/results/rdd/rdd_fuzzy_coverage.csv
@@ -1,99 +1,99 @@
 Method,fs specification,Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-rdflex,cutoff,Global linear,Global linear,0.9,0.8,14.423037908091597,3.2637402601909544,5
-rdflex,cutoff,Global linear,Global linear,0.95,1.0,17.186109684366134,3.2637402601909544,5
-rdflex,cutoff,Global linear,LGBM,0.9,1.0,9.60760402812852,2.610897383935538,5
-rdflex,cutoff,Global linear,LGBM,0.95,1.0,11.448166307511448,2.610897383935538,5
-rdflex,cutoff,Global linear,Linear,0.9,1.0,14.226538661834956,3.3206952967859835,5
-rdflex,cutoff,Global linear,Linear,0.95,1.0,16.95196639079777,3.3206952967859835,5
-rdflex,cutoff,Global linear,Stacked,0.9,1.0,11.479292659550719,2.892434062670725,5
-rdflex,cutoff,Global linear,Stacked,0.95,1.0,13.678420871049463,2.892434062670725,5
-rdflex,cutoff,LGBM,Global linear,0.9,1.0,2.291086593513875,0.3217115365585489,5
-rdflex,cutoff,LGBM,Global linear,0.95,1.0,2.729998058898547,0.3217115365585489,5
-rdflex,cutoff,LGBM,LGBM,0.9,1.0,1.8232352455660876,0.471335656388427,5
-rdflex,cutoff,LGBM,LGBM,0.95,1.0,2.172518793223295,0.471335656388427,5
-rdflex,cutoff,LGBM,Linear,0.9,1.0,2.5036910885538886,0.46592543647375206,5
-rdflex,cutoff,LGBM,Linear,0.95,1.0,2.983331940042759,0.46592543647375206,5
-rdflex,cutoff,LGBM,Stacked,0.9,1.0,1.983251590128728,0.3648095017291908,5
-rdflex,cutoff,LGBM,Stacked,0.95,1.0,2.3631900281232623,0.3648095017291908,5
-rdflex,cutoff,Linear,Global linear,0.9,0.8,13.898849040803778,3.2754800847865724,5
-rdflex,cutoff,Linear,Global linear,0.95,1.0,16.56150012388803,3.2754800847865724,5
-rdflex,cutoff,Linear,LGBM,0.9,1.0,8.788094435735177,2.454463244345884,5
-rdflex,cutoff,Linear,LGBM,0.95,1.0,10.471660398561387,2.454463244345884,5
-rdflex,cutoff,Linear,Linear,0.9,0.8,14.47344689140013,3.3491813910739134,5
-rdflex,cutoff,Linear,Linear,0.95,1.0,17.246175692771462,3.3491813910739134,5
-rdflex,cutoff,Linear,Stacked,0.9,1.0,10.558846700439386,2.764041856725428,5
-rdflex,cutoff,Linear,Stacked,0.95,1.0,12.581641862866709,2.764041856725428,5
-rdflex,cutoff,Stacked,Global linear,0.9,0.8,2.4355448606892423,0.3881680057707292,5
-rdflex,cutoff,Stacked,Global linear,0.95,1.0,2.9021307011553152,0.3881680057707292,5
-rdflex,cutoff,Stacked,LGBM,0.9,1.0,1.7612830354582933,0.43067758587432187,5
-rdflex,cutoff,Stacked,LGBM,0.95,1.0,2.09869818172063,0.43067758587432187,5
-rdflex,cutoff,Stacked,Linear,0.9,1.0,2.0422134023298866,0.21267147182739804,5
-rdflex,cutoff,Stacked,Linear,0.95,1.0,2.433447360741768,0.21267147182739804,5
-rdflex,cutoff,Stacked,Stacked,0.9,0.8,2.0563286274932917,0.5572667177929984,5
-rdflex,cutoff,Stacked,Stacked,0.95,0.8,2.4502666889182345,0.5572667177929984,5
-rdflex,cutoff and score,Global linear,Global linear,0.9,1.0,14.259416097319534,3.29291711658142,5
-rdflex,cutoff and score,Global linear,Global linear,0.95,1.0,16.991142271494972,3.29291711658142,5
-rdflex,cutoff and score,Global linear,LGBM,0.9,1.0,11.497486915431436,2.866354293380936,5
-rdflex,cutoff and score,Global linear,LGBM,0.95,1.0,13.70010066411275,2.866354293380936,5
-rdflex,cutoff and score,Global linear,Linear,0.9,1.0,14.322347851500998,3.297628178611928,5
-rdflex,cutoff and score,Global linear,Linear,0.95,1.0,17.066130081752714,3.297628178611928,5
-rdflex,cutoff and score,Global linear,Stacked,0.9,1.0,11.187221250336403,2.8665327874888407,5
-rdflex,cutoff and score,Global linear,Stacked,0.95,1.0,13.33039632126938,2.8665327874888407,5
-rdflex,cutoff and score,LGBM,Global linear,0.9,1.0,2.132646705302484,0.35115271453669183,5
-rdflex,cutoff and score,LGBM,Global linear,0.95,1.0,2.5412052876022835,0.35115271453669183,5
-rdflex,cutoff and score,LGBM,LGBM,0.9,1.0,1.651573825829961,0.49015621894821504,5
-rdflex,cutoff and score,LGBM,LGBM,0.95,1.0,1.9679715954027883,0.49015621894821504,5
-rdflex,cutoff and score,LGBM,Linear,0.9,1.0,2.0653982476186394,0.33633981978688077,5
-rdflex,cutoff and score,LGBM,Linear,0.95,1.0,2.4610738078666157,0.33633981978688077,5
-rdflex,cutoff and score,LGBM,Stacked,0.9,1.0,2.070887518085169,0.48315068117208615,5
-rdflex,cutoff and score,LGBM,Stacked,0.95,1.0,2.4676146770597835,0.48315068117208615,5
-rdflex,cutoff and score,Linear,Global linear,0.9,0.8,13.834500877512358,3.252602683579687,5
-rdflex,cutoff and score,Linear,Global linear,0.95,1.0,16.484824558077207,3.252602683579687,5
-rdflex,cutoff and score,Linear,LGBM,0.9,1.0,11.021494973340559,2.957462426090728,5
-rdflex,cutoff and score,Linear,LGBM,0.95,1.0,13.132921282225468,2.957462426090728,5
-rdflex,cutoff and score,Linear,Linear,0.9,0.8,13.565400587199502,3.273961937011743,5
-rdflex,cutoff and score,Linear,Linear,0.95,1.0,16.16417178472376,3.273961937011743,5
-rdflex,cutoff and score,Linear,Stacked,0.9,1.0,9.781507067833797,2.5759545181110926,5
-rdflex,cutoff and score,Linear,Stacked,0.95,1.0,11.655384560272386,2.5759545181110926,5
-rdflex,cutoff and score,Stacked,Global linear,0.9,0.8,1.9443850931574904,0.35287630976386913,5
-rdflex,cutoff and score,Stacked,Global linear,0.95,1.0,2.3168777405004146,0.35287630976386913,5
-rdflex,cutoff and score,Stacked,LGBM,0.9,1.0,1.5606416431884977,0.27407774182095623,5
-rdflex,cutoff and score,Stacked,LGBM,0.95,1.0,1.8596192167518069,0.27407774182095623,5
-rdflex,cutoff and score,Stacked,Linear,0.9,1.0,2.193836968365324,0.3692120996481659,5
-rdflex,cutoff and score,Stacked,Linear,0.95,1.0,2.614117983201815,0.3692120996481659,5
-rdflex,cutoff and score,Stacked,Stacked,0.9,1.0,1.8666724118484936,0.5368999174526484,5
-rdflex,cutoff and score,Stacked,Stacked,0.95,1.0,2.2242773692503803,0.5368999174526484,5
-rdflex,interacted cutoff and score,Global linear,Global linear,0.9,0.8,11.50038602288641,2.8517535553634956,5
-rdflex,interacted cutoff and score,Global linear,Global linear,0.95,1.0,13.703555163714393,2.8517535553634956,5
-rdflex,interacted cutoff and score,Global linear,LGBM,0.9,1.0,10.315801252711834,2.7007313341878936,5
-rdflex,interacted cutoff and score,Global linear,LGBM,0.95,1.0,12.292035349346543,2.7007313341878936,5
-rdflex,interacted cutoff and score,Global linear,Linear,0.9,0.8,11.729502101422899,2.9285377690970025,5
-rdflex,interacted cutoff and score,Global linear,Linear,0.95,1.0,13.976563810108567,2.9285377690970025,5
-rdflex,interacted cutoff and score,Global linear,Stacked,0.9,1.0,10.084512037249876,2.6635463803766095,5
-rdflex,interacted cutoff and score,Global linear,Stacked,0.95,1.0,12.016437250591622,2.6635463803766095,5
-rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.8,2.4613080577042163,0.6177915730998491,5
-rdflex,interacted cutoff and score,LGBM,Global linear,0.95,0.8,2.932829443857146,0.6177915730998491,5
-rdflex,interacted cutoff and score,LGBM,LGBM,0.9,1.0,1.9380473017675328,0.3240944835816227,5
-rdflex,interacted cutoff and score,LGBM,LGBM,0.95,1.0,2.3093257962651896,0.3240944835816227,5
-rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.8,2.3048779458142628,0.3381467569608999,5
-rdflex,interacted cutoff and score,LGBM,Linear,0.95,1.0,2.7464314687557887,0.3381467569608999,5
-rdflex,interacted cutoff and score,LGBM,Stacked,0.9,1.0,1.9806236593394437,0.34797999285711156,5
-rdflex,interacted cutoff and score,LGBM,Stacked,0.95,1.0,2.36005865544884,0.34797999285711156,5
-rdflex,interacted cutoff and score,Linear,Global linear,0.9,0.8,14.980877656814286,3.4800582831380575,5
-rdflex,interacted cutoff and score,Linear,Global linear,0.95,1.0,17.85081674323539,3.4800582831380575,5
-rdflex,interacted cutoff and score,Linear,LGBM,0.9,1.0,9.140955749697142,2.5395424847293753,5
-rdflex,interacted cutoff and score,Linear,LGBM,0.95,1.0,10.892120587584234,2.5395424847293753,5
-rdflex,interacted cutoff and score,Linear,Linear,0.9,0.8,15.4138192982352,3.6678662653096916,5
-rdflex,interacted cutoff and score,Linear,Linear,0.95,1.0,18.366698527905392,3.6678662653096916,5
-rdflex,interacted cutoff and score,Linear,Stacked,0.9,1.0,10.864595627804398,2.894493634370918,5
-rdflex,interacted cutoff and score,Linear,Stacked,0.95,1.0,12.945964180748467,2.894493634370918,5
-rdflex,interacted cutoff and score,Stacked,Global linear,0.9,1.0,2.421350027458176,0.2543821651969947,5
-rdflex,interacted cutoff and score,Stacked,Global linear,0.95,1.0,2.885216514115459,0.2543821651969947,5
-rdflex,interacted cutoff and score,Stacked,LGBM,0.9,1.0,1.9090916620591405,0.5916268970924577,5
-rdflex,interacted cutoff and score,Stacked,LGBM,0.95,1.0,2.274823023466525,0.5916268970924577,5
-rdflex,interacted cutoff and score,Stacked,Linear,0.9,1.0,2.4287704707086424,0.42238035779134736,5
-rdflex,interacted cutoff and score,Stacked,Linear,0.95,1.0,2.8940585176116564,0.42238035779134736,5
-rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.8,2.3752766407951578,0.5905486473170087,5
-rdflex,interacted cutoff and score,Stacked,Stacked,0.95,1.0,2.830316687756643,0.5905486473170087,5
-rdrobust,cutoff,linear,linear,0.9,1.0,13.247577083256981,2.876321200969484,5
-rdrobust,cutoff,linear,linear,0.95,1.0,15.785461721432487,2.876321200969484,5
+rdflex,cutoff,Global linear,Global linear,0.9,0.93,9.081392906274068,2.1933385393109197,200
+rdflex,cutoff,Global linear,Global linear,0.95,0.975,10.821147082092207,2.1933385393109197,200
+rdflex,cutoff,Global linear,LGBM,0.9,0.945,9.071374045045866,2.261373434009399,200
+rdflex,cutoff,Global linear,LGBM,0.95,0.985,10.809208872605582,2.261373434009399,200
+rdflex,cutoff,Global linear,Linear,0.9,0.94,9.18803129264423,2.2181198604056123,200
+rdflex,cutoff,Global linear,Linear,0.95,0.97,10.948214556808693,2.2181198604056123,200
+rdflex,cutoff,Global linear,Stacked,0.9,0.935,8.990034820220394,2.2441214304905195,200
+rdflex,cutoff,Global linear,Stacked,0.95,0.975,10.712287208223932,2.2441214304905195,200
+rdflex,cutoff,LGBM,Global linear,0.9,0.92,1.6916778730210564,0.3944842423890586,200
+rdflex,cutoff,LGBM,Global linear,0.95,0.985,2.0157585150659814,0.3944842423890586,200
+rdflex,cutoff,LGBM,LGBM,0.9,0.95,1.615800542441541,0.3719114314569723,200
+rdflex,cutoff,LGBM,LGBM,0.95,0.98,1.925345099098679,0.3719114314569723,200
+rdflex,cutoff,LGBM,Linear,0.9,0.94,1.6965648079234554,0.38597937057745973,200
+rdflex,cutoff,LGBM,Linear,0.95,0.99,2.021581657166015,0.38597937057745973,200
+rdflex,cutoff,LGBM,Stacked,0.9,0.935,1.593452293167818,0.33657448062658235,200
+rdflex,cutoff,LGBM,Stacked,0.95,0.985,1.898715517611114,0.33657448062658235,200
+rdflex,cutoff,Linear,Global linear,0.9,0.93,9.075817172665094,2.199047016932969,200
+rdflex,cutoff,Linear,Global linear,0.95,0.975,10.814503185710231,2.199047016932969,200
+rdflex,cutoff,Linear,LGBM,0.9,0.945,9.006421996493895,2.2499576335207867,200
+rdflex,cutoff,Linear,LGBM,0.95,0.975,10.731813733124445,2.2499576335207867,200
+rdflex,cutoff,Linear,Linear,0.9,0.93,9.19023631539689,2.2324898070695376,200
+rdflex,cutoff,Linear,Linear,0.95,0.975,10.95084200347598,2.2324898070695376,200
+rdflex,cutoff,Linear,Stacked,0.9,0.93,8.868858682952633,2.170604197519602,200
+rdflex,cutoff,Linear,Stacked,0.95,0.98,10.567896934865278,2.170604197519602,200
+rdflex,cutoff,Stacked,Global linear,0.9,0.94,1.7082355652914638,0.3858776284107599,200
+rdflex,cutoff,Stacked,Global linear,0.95,0.99,2.0354882223088335,0.3858776284107599,200
+rdflex,cutoff,Stacked,LGBM,0.9,0.95,1.6152877419864777,0.38023115554419357,200
+rdflex,cutoff,Stacked,LGBM,0.95,0.97,1.9247340596683542,0.38023115554419357,200
+rdflex,cutoff,Stacked,Linear,0.9,0.9,1.7085892928386948,0.38715972085633743,200
+rdflex,cutoff,Stacked,Linear,0.95,0.96,2.0359097146784597,0.38715972085633743,200
+rdflex,cutoff,Stacked,Stacked,0.9,0.955,1.6143624078750711,0.3399797304777219,200
+rdflex,cutoff,Stacked,Stacked,0.95,0.975,1.9236314560674583,0.3399797304777219,200
+rdflex,cutoff and score,Global linear,Global linear,0.9,0.945,9.080075892369969,2.1932099043718005,200
+rdflex,cutoff and score,Global linear,Global linear,0.95,0.97,10.819577763231928,2.1932099043718005,200
+rdflex,cutoff and score,Global linear,LGBM,0.9,0.955,9.123861848035432,2.26628855189193,200
+rdflex,cutoff and score,Global linear,LGBM,0.95,0.98,10.871751947443094,2.26628855189193,200
+rdflex,cutoff and score,Global linear,Linear,0.9,0.94,9.161670882012661,2.2100071846242657,200
+rdflex,cutoff and score,Global linear,Linear,0.95,0.97,10.916804190190655,2.2100071846242657,200
+rdflex,cutoff and score,Global linear,Stacked,0.9,0.945,9.12900517734864,2.234311195114868,200
+rdflex,cutoff and score,Global linear,Stacked,0.95,0.975,10.877880602327238,2.234311195114868,200
+rdflex,cutoff and score,LGBM,Global linear,0.9,0.975,1.7677213444582995,0.3895705364821883,200
+rdflex,cutoff and score,LGBM,Global linear,0.95,0.99,2.1063699000757397,0.3895705364821883,200
+rdflex,cutoff and score,LGBM,LGBM,0.9,0.955,1.7097986739938167,0.3989682200244538,200
+rdflex,cutoff and score,LGBM,LGBM,0.95,0.975,2.0373507812078957,0.3989682200244538,200
+rdflex,cutoff and score,LGBM,Linear,0.9,0.95,1.7436698369090557,0.3896899920948269,200
+rdflex,cutoff and score,LGBM,Linear,0.95,0.98,2.0777107611724324,0.3896899920948269,200
+rdflex,cutoff and score,LGBM,Stacked,0.9,0.945,1.6921819422814257,0.3976386225783639,200
+rdflex,cutoff and score,LGBM,Stacked,0.95,0.985,2.0163591506361316,0.3976386225783639,200
+rdflex,cutoff and score,Linear,Global linear,0.9,0.935,9.140994535035215,2.2292520538999314,200
+rdflex,cutoff and score,Linear,Global linear,0.95,0.975,10.892166803165066,2.2292520538999314,200
+rdflex,cutoff and score,Linear,LGBM,0.9,0.945,9.230547983693715,2.2907915601909408,200
+rdflex,cutoff and score,Linear,LGBM,0.95,0.98,10.9988763189457,2.2907915601909408,200
+rdflex,cutoff and score,Linear,Linear,0.9,0.925,9.159848674913668,2.2075015174066497,200
+rdflex,cutoff and score,Linear,Linear,0.95,0.975,10.914632896509636,2.2075015174066497,200
+rdflex,cutoff and score,Linear,Stacked,0.9,0.935,8.986928535062534,2.2429319842794295,200
+rdflex,cutoff and score,Linear,Stacked,0.95,0.975,10.708585841162837,2.2429319842794295,200
+rdflex,cutoff and score,Stacked,Global linear,0.9,0.91,1.776522112039948,0.39332706585160665,200
+rdflex,cutoff and score,Stacked,Global linear,0.95,0.97,2.1168566614590656,0.39332706585160665,200
+rdflex,cutoff and score,Stacked,LGBM,0.9,0.925,1.709515895023752,0.4026131018857037,200
+rdflex,cutoff and score,Stacked,LGBM,0.95,0.975,2.037013829282307,0.4026131018857037,200
+rdflex,cutoff and score,Stacked,Linear,0.9,0.945,1.7808563057254776,0.4007040458728064,200
+rdflex,cutoff and score,Stacked,Linear,0.95,0.995,2.122021171775648,0.4007040458728064,200
+rdflex,cutoff and score,Stacked,Stacked,0.9,0.925,1.74556578243726,0.39512341857753314,200
+rdflex,cutoff and score,Stacked,Stacked,0.95,0.98,2.0799699196112393,0.39512341857753314,200
+rdflex,interacted cutoff and score,Global linear,Global linear,0.9,0.93,9.061017454676579,2.180506418406957,200
+rdflex,interacted cutoff and score,Global linear,Global linear,0.95,0.975,10.796868234026052,2.180506418406957,200
+rdflex,interacted cutoff and score,Global linear,LGBM,0.9,0.945,9.191021529436847,2.2563449662547352,200
+rdflex,interacted cutoff and score,Global linear,LGBM,0.95,0.97,10.951777643713662,2.2563449662547352,200
+rdflex,interacted cutoff and score,Global linear,Linear,0.9,0.935,9.167705084002202,2.2186339606032286,200
+rdflex,interacted cutoff and score,Global linear,Linear,0.95,0.975,10.923994385343072,2.2186339606032286,200
+rdflex,interacted cutoff and score,Global linear,Stacked,0.9,0.955,8.984109518341889,2.215893099200206,200
+rdflex,interacted cutoff and score,Global linear,Stacked,0.95,0.975,10.705226775557394,2.215893099200206,200
+rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.95,1.78003628124215,0.40021895592964696,200
+rdflex,interacted cutoff and score,LGBM,Global linear,0.95,0.985,2.121044052336308,0.40021895592964696,200
+rdflex,interacted cutoff and score,LGBM,LGBM,0.9,0.945,1.7352078615081552,0.3682890431886914,200
+rdflex,interacted cutoff and score,LGBM,LGBM,0.95,0.98,2.0676276955718977,0.3682890431886914,200
+rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.94,1.7626227479121315,0.38482868938106907,200
+rdflex,interacted cutoff and score,LGBM,Linear,0.95,0.985,2.1002945475711456,0.38482868938106907,200
+rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.93,1.7237010890318276,0.4070129098798606,200
+rdflex,interacted cutoff and score,LGBM,Stacked,0.95,0.99,2.0539165304795377,0.4070129098798606,200
+rdflex,interacted cutoff and score,Linear,Global linear,0.9,0.93,9.196222925824271,2.2332568020997727,200
+rdflex,interacted cutoff and score,Linear,Global linear,0.95,0.975,10.957975489784355,2.2332568020997727,200
+rdflex,interacted cutoff and score,Linear,LGBM,0.9,0.945,9.261389340916475,2.2694537643554695,200
+rdflex,interacted cutoff and score,Linear,LGBM,0.95,0.97,11.035626062752984,2.2694537643554695,200
+rdflex,interacted cutoff and score,Linear,Linear,0.9,0.93,9.263515375167458,2.2377624722965814,200
+rdflex,interacted cutoff and score,Linear,Linear,0.95,0.975,11.038159388815284,2.2377624722965814,200
+rdflex,interacted cutoff and score,Linear,Stacked,0.9,0.95,9.123427141504681,2.266717454845839,200
+rdflex,interacted cutoff and score,Linear,Stacked,0.95,0.975,10.87123396266308,2.266717454845839,200
+rdflex,interacted cutoff and score,Stacked,Global linear,0.9,0.955,1.81336839938933,0.38591136894636113,200
+rdflex,interacted cutoff and score,Stacked,Global linear,0.95,0.97,2.1607617208427676,0.38591136894636113,200
+rdflex,interacted cutoff and score,Stacked,LGBM,0.9,0.935,1.7411337194500436,0.3926129635572617,200
+rdflex,interacted cutoff and score,Stacked,LGBM,0.95,0.97,2.0746887908288216,0.3926129635572617,200
+rdflex,interacted cutoff and score,Stacked,Linear,0.9,0.935,1.8383865669851245,0.39956163215234425,200
+rdflex,interacted cutoff and score,Stacked,Linear,0.95,0.965,2.190572706235933,0.39956163215234425,200
+rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.935,1.772193337511724,0.38945684216992094,200
+rdflex,interacted cutoff and score,Stacked,Stacked,0.95,0.985,2.1116986084666918,0.38945684216992094,200
+rdrobust,cutoff,linear,linear,0.9,0.935,10.477786198433689,2.22067665589711,200
+rdrobust,cutoff,linear,linear,0.95,0.97,12.485052317209465,2.22067665589711,200
diff --git a/results/rdd/rdd_fuzzy_coverage_metadata.csv b/results/rdd/rdd_fuzzy_coverage_metadata.csv
index 49bcf8c..a19ddd2 100644
--- a/results/rdd/rdd_fuzzy_coverage_metadata.csv
+++ b/results/rdd/rdd_fuzzy_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_fuzzy_coverage.py,2024-10-14 08:24:15,310.4044132232666,3.12.7
+0.9.dev0,rdd_fuzzy_coverage.py,2024-10-14 11:56:14,12188.346573114395,3.12.7

From 12cd9aaa7303908eade6cbaa585eefb5c28552f8 Mon Sep 17 00:00:00 2001
From: Sven Klaassen <47529404+SvenKlaassen@users.noreply.github.com>
Date: Tue, 15 Oct 2024 10:44:02 +0200
Subject: [PATCH 18/58] update coefs to robust

---
 scripts/rdd/rdd_fuzzy_coverage.py | 10 +++++-----
 scripts/rdd/rdd_sharp_coverage.py | 10 +++++-----
 2 files changed, 10 insertions(+), 10 deletions(-)

diff --git a/scripts/rdd/rdd_fuzzy_coverage.py b/scripts/rdd/rdd_fuzzy_coverage.py
index 271afea..5ec5491 100644
--- a/scripts/rdd/rdd_fuzzy_coverage.py
+++ b/scripts/rdd/rdd_fuzzy_coverage.py
@@ -91,7 +91,7 @@
     # baseline
     for level_idx, level in enumerate(hyperparam_dict["level"]):
         res = rdrobust(y=Y, x=score, fuzzy=D, covs=Z, c=cutoff, level=level*100)
-        coef = res.coef.loc["Conventional", "Coeff"]
+        coef = res.coef.loc["Robust", "Coeff"]
         ci_lower = res.ci.loc["Robust", "CI Lower"]
         ci_upper = res.ci.loc["Robust", "CI Upper"]
 
@@ -131,15 +131,15 @@
 
                 for level_idx, level in enumerate(hyperparam_dict["level"]):
                     confint = rdflex_model.confint(level=level)
-                    coverage = (confint.iloc[0, 0] < oracle_effect) & (oracle_effect < confint.iloc[0, 1])
-                    ci_length = confint.iloc[0, 1] - confint.iloc[0, 0]
+                    coverage = (confint.iloc[2, 0] < oracle_effect) & (oracle_effect < confint.iloc[2, 1])
+                    ci_length = confint.iloc[2, 1] - confint.iloc[2, 0]
 
                     df_results_detailed = pd.concat(
                         (df_results_detailed,
                             pd.DataFrame({
                                 "Coverage": coverage.astype(int),
-                                "CI Length": confint.iloc[0, 1] - confint.iloc[0, 0],
-                                "Bias": abs(rdflex_model.coef[0] - oracle_effect),
+                                "CI Length": ci_length,
+                                "Bias": abs(rdflex_model.coef[2] - oracle_effect),
                                 "Learner g": learner_g_name,
                                 "Learner m": learner_m_name,
                                 "Method": "rdflex",
diff --git a/scripts/rdd/rdd_sharp_coverage.py b/scripts/rdd/rdd_sharp_coverage.py
index eb528d1..30d5d95 100644
--- a/scripts/rdd/rdd_sharp_coverage.py
+++ b/scripts/rdd/rdd_sharp_coverage.py
@@ -80,7 +80,7 @@
     # baseline
     for level_idx, level in enumerate(hyperparam_dict["level"]):
         res = rdrobust(y=Y, x=score, covs=Z, c=cutoff, level=level*100)
-        coef = res.coef.loc["Conventional", "Coeff"]
+        coef = res.coef.loc["Robust", "Coeff"]
         ci_lower = res.ci.loc["Robust", "CI Lower"]
         ci_upper = res.ci.loc["Robust", "CI Upper"]
 
@@ -117,15 +117,15 @@
 
             for level_idx, level in enumerate(hyperparam_dict["level"]):
                 confint = rdflex_model.confint(level=level)
-                coverage = (confint.iloc[0, 0] < oracle_effect) & (oracle_effect < confint.iloc[0, 1])
-                ci_length = confint.iloc[0, 1] - confint.iloc[0, 0]
+                coverage = (confint.iloc[2, 0] < oracle_effect) & (oracle_effect < confint.iloc[2, 1])
+                ci_length = confint.iloc[2, 1] - confint.iloc[2, 0]
 
                 df_results_detailed = pd.concat(
                     (df_results_detailed,
                         pd.DataFrame({
                             "Coverage": coverage.astype(int),
-                            "CI Length": confint.iloc[0, 1] - confint.iloc[0, 0],
-                            "Bias": abs(rdflex_model.coef[0] - oracle_effect),
+                            "CI Length": ci_length,
+                            "Bias": abs(rdflex_model.coef[2] - oracle_effect),
                             "Learner g": learner_g_name,
                             "Method": "rdflex",
                             "fs specification": fs_specification,

From b7ff546ab95f6dd45abf1c130c2c7198e6545080 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Tue, 15 Oct 2024 09:14:30 +0000
Subject: [PATCH 19/58] Update results from script:
 scripts/rdd/rdd_sharp_coverage.py

---
 results/rdd/rdd_sharp_coverage.csv          | 52 ++++++++++-----------
 results/rdd/rdd_sharp_coverage_metadata.csv |  2 +-
 2 files changed, 27 insertions(+), 27 deletions(-)

diff --git a/results/rdd/rdd_sharp_coverage.csv b/results/rdd/rdd_sharp_coverage.csv
index d5617c2..c7c123f 100644
--- a/results/rdd/rdd_sharp_coverage.csv
+++ b/results/rdd/rdd_sharp_coverage.csv
@@ -1,27 +1,27 @@
 Method,fs specification,Learner g,level,Coverage,CI Length,Bias,repetition
-rdflex,cutoff,Global linear,0.9,0.845,1.866210870042375,0.5038360519795877,200
-rdflex,cutoff,Global linear,0.95,0.885,2.223727408267512,0.5038360519795877,200
-rdflex,cutoff,LGBM,0.9,0.875,0.46812541151643167,0.12861132896027008,200
-rdflex,cutoff,LGBM,0.95,0.92,0.5578058325595114,0.12861132896027008,200
-rdflex,cutoff,Linear,0.9,0.84,1.8736415637299357,0.5135146512043519,200
-rdflex,cutoff,Linear,0.95,0.88,2.23258162591286,0.5135146512043519,200
-rdflex,cutoff,Stacked,0.9,0.865,0.4595500872797082,0.1257126877847947,200
-rdflex,cutoff,Stacked,0.95,0.93,0.5475877034905549,0.1257126877847947,200
-rdflex,cutoff and score,Global linear,0.9,0.85,1.8654996931859682,0.5051156412170476,200
-rdflex,cutoff and score,Global linear,0.95,0.88,2.222879988775372,0.5051156412170476,200
-rdflex,cutoff and score,LGBM,0.9,0.865,0.4800927111671489,0.1267152246127786,200
-rdflex,cutoff and score,LGBM,0.95,0.945,0.5720657496264642,0.1267152246127786,200
-rdflex,cutoff and score,Linear,0.9,0.85,1.8717967972330274,0.5120276627581323,200
-rdflex,cutoff and score,Linear,0.95,0.89,2.2303834510512295,0.5120276627581323,200
-rdflex,cutoff and score,Stacked,0.9,0.84,0.4705945727392839,0.13524794362256828,200
-rdflex,cutoff and score,Stacked,0.95,0.92,0.5607480196268084,0.13524794362256828,200
-rdflex,interacted cutoff and score,Global linear,0.9,0.84,1.8688480818750401,0.5042547628696261,200
-rdflex,interacted cutoff and score,Global linear,0.95,0.895,2.2268698399872306,0.5042547628696261,200
-rdflex,interacted cutoff and score,LGBM,0.9,0.825,0.48245074981985836,0.1364434399455555,200
-rdflex,interacted cutoff and score,LGBM,0.95,0.905,0.574875525984516,0.1364434399455555,200
-rdflex,interacted cutoff and score,Linear,0.9,0.84,1.8808660437088858,0.5104091884554597,200
-rdflex,interacted cutoff and score,Linear,0.95,0.885,2.241190124768783,0.5104091884554597,200
-rdflex,interacted cutoff and score,Stacked,0.9,0.85,0.4797858036570431,0.1377828475018157,200
-rdflex,interacted cutoff and score,Stacked,0.95,0.9,0.5717000467720971,0.1377828475018157,200
-rdrobust,cutoff,linear,0.9,0.84,2.184383574713776,0.5092603596094496,200
-rdrobust,cutoff,linear,0.95,0.895,2.602853569891644,0.5092603596094496,200
+rdflex,cutoff,Global linear,0.9,0.85,2.2038817328826754,0.5781853469884299,200
+rdflex,cutoff,Global linear,0.95,0.895,2.626087058361215,0.5781853469884299,200
+rdflex,cutoff,LGBM,0.9,0.9,0.5489293795795934,0.14138881305826245,200
+rdflex,cutoff,LGBM,0.95,0.94,0.654089699170333,0.14138881305826245,200
+rdflex,cutoff,Linear,0.9,0.85,2.212426058297747,0.5869505014882239,200
+rdflex,cutoff,Linear,0.95,0.9,2.6362682500559247,0.5869505014882239,200
+rdflex,cutoff,Stacked,0.9,0.89,0.5401104795583865,0.13671196195207622,200
+rdflex,cutoff,Stacked,0.95,0.935,0.6435813316526349,0.13671196195207622,200
+rdflex,cutoff and score,Global linear,0.9,0.855,2.2031794642927314,0.5803760017012753,200
+rdflex,cutoff and score,Global linear,0.95,0.9,2.625250253723276,0.5803760017012753,200
+rdflex,cutoff and score,LGBM,0.9,0.91,0.5661903205762662,0.14041644950018034,200
+rdflex,cutoff and score,LGBM,0.95,0.95,0.6746573789555858,0.14041644950018034,200
+rdflex,cutoff and score,Linear,0.9,0.85,2.210257349249581,0.5861956425526764,200
+rdflex,cutoff and score,Linear,0.95,0.9,2.63368407383641,0.5861956425526764,200
+rdflex,cutoff and score,Stacked,0.9,0.865,0.5526668555917932,0.15053840369931945,200
+rdflex,cutoff and score,Stacked,0.95,0.91,0.6585431765235554,0.15053840369931945,200
+rdflex,interacted cutoff and score,Global linear,0.9,0.855,2.2067448709410886,0.5796586405457141,200
+rdflex,interacted cutoff and score,Global linear,0.95,0.9,2.6294986977832933,0.5796586405457141,200
+rdflex,interacted cutoff and score,LGBM,0.9,0.87,0.5675129418312119,0.1515231799200044,200
+rdflex,interacted cutoff and score,LGBM,0.95,0.92,0.676233379386509,0.1515231799200044,200
+rdflex,interacted cutoff and score,Linear,0.9,0.855,2.2209084131452888,0.5832381244405058,200
+rdflex,interacted cutoff and score,Linear,0.95,0.895,2.6463755992649136,0.5832381244405058,200
+rdflex,interacted cutoff and score,Stacked,0.9,0.84,0.5635026024806519,0.1540631695077759,200
+rdflex,interacted cutoff and score,Stacked,0.95,0.93,0.6714547653116205,0.1540631695077759,200
+rdrobust,cutoff,linear,0.9,0.84,2.184383574713776,0.585928851003536,200
+rdrobust,cutoff,linear,0.95,0.895,2.602853569891644,0.585928851003536,200
diff --git a/results/rdd/rdd_sharp_coverage_metadata.csv b/results/rdd/rdd_sharp_coverage_metadata.csv
index f84517e..9815438 100644
--- a/results/rdd/rdd_sharp_coverage_metadata.csv
+++ b/results/rdd/rdd_sharp_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_sharp_coverage.py,2024-10-14 09:00:22,1636.632357597351,3.12.7
+0.9.dev0,rdd_sharp_coverage.py,2024-10-15 09:14:30,1643.302789926529,3.12.7

From b970c920d5c3cbd37a09fc0a42ff178c98ec9108 Mon Sep 17 00:00:00 2001
From: Sven Klaassen <47529404+SvenKlaassen@users.noreply.github.com>
Date: Tue, 15 Oct 2024 13:33:18 +0200
Subject: [PATCH 20/58] add rdd

---
 doc/_website.yml | 16 +++++++++-------
 1 file changed, 9 insertions(+), 7 deletions(-)

diff --git a/doc/_website.yml b/doc/_website.yml
index 7bd5b90..6dd3260 100644
--- a/doc/_website.yml
+++ b/doc/_website.yml
@@ -1,7 +1,7 @@
 website:
   title: "DoubleML Coverage"
   favicon: _static/favicon.ico
-  search: 
+  search:
     location: sidebar
   sidebar:
     style: "docked"
@@ -18,20 +18,23 @@ website:
           - irm/apo.qmd
           - irm/qte.qmd
       - text: "PLM"
-        menu:      
+        menu:
           - plm/plr.qmd
           - plm/plr_gate.qmd
           - plm/plr_cate.qmd
           - plm/pliv.qmd
       - text: "DID"
-        menu:      
+        menu:
           - did/did_pa.qmd
           - did/did_cs.qmd
       - text: "SSM"
-        menu:      
+        menu:
           - ssm/ssm_mar.qmd
           - ssm/ssm_nonignorable.qmd
-    right: 
+      - text: "RDD"
+        menu:
+          - rdd/rdd.qmd
+    right:
       - icon: book
         href: https://docs.doubleml.org/stable/index.html
         aria-label: Documentation
@@ -43,9 +46,8 @@ website:
             href: https://github.com/DoubleML/doubleml-coverage
         aria-label: GitHub
 
-
 format:
   html:
-    theme: cosmo 
+    theme: cosmo
     css: styles.css
     toc: true

From 3a2ab4dbdc83bcaff79f736dee0f1e504ab66262 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Tue, 15 Oct 2024 12:05:47 +0000
Subject: [PATCH 21/58] Update results from script:
 scripts/rdd/rdd_fuzzy_coverage.py

---
 results/rdd/rdd_fuzzy_coverage.csv          | 196 ++++++++++----------
 results/rdd/rdd_fuzzy_coverage_metadata.csv |   2 +-
 2 files changed, 99 insertions(+), 99 deletions(-)

diff --git a/results/rdd/rdd_fuzzy_coverage.csv b/results/rdd/rdd_fuzzy_coverage.csv
index f1ce596..b9643bf 100644
--- a/results/rdd/rdd_fuzzy_coverage.csv
+++ b/results/rdd/rdd_fuzzy_coverage.csv
@@ -1,99 +1,99 @@
 Method,fs specification,Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-rdflex,cutoff,Global linear,Global linear,0.9,0.93,9.081392906274068,2.1933385393109197,200
-rdflex,cutoff,Global linear,Global linear,0.95,0.975,10.821147082092207,2.1933385393109197,200
-rdflex,cutoff,Global linear,LGBM,0.9,0.945,9.071374045045866,2.261373434009399,200
-rdflex,cutoff,Global linear,LGBM,0.95,0.985,10.809208872605582,2.261373434009399,200
-rdflex,cutoff,Global linear,Linear,0.9,0.94,9.18803129264423,2.2181198604056123,200
-rdflex,cutoff,Global linear,Linear,0.95,0.97,10.948214556808693,2.2181198604056123,200
-rdflex,cutoff,Global linear,Stacked,0.9,0.935,8.990034820220394,2.2441214304905195,200
-rdflex,cutoff,Global linear,Stacked,0.95,0.975,10.712287208223932,2.2441214304905195,200
-rdflex,cutoff,LGBM,Global linear,0.9,0.92,1.6916778730210564,0.3944842423890586,200
-rdflex,cutoff,LGBM,Global linear,0.95,0.985,2.0157585150659814,0.3944842423890586,200
-rdflex,cutoff,LGBM,LGBM,0.9,0.95,1.615800542441541,0.3719114314569723,200
-rdflex,cutoff,LGBM,LGBM,0.95,0.98,1.925345099098679,0.3719114314569723,200
-rdflex,cutoff,LGBM,Linear,0.9,0.94,1.6965648079234554,0.38597937057745973,200
-rdflex,cutoff,LGBM,Linear,0.95,0.99,2.021581657166015,0.38597937057745973,200
-rdflex,cutoff,LGBM,Stacked,0.9,0.935,1.593452293167818,0.33657448062658235,200
-rdflex,cutoff,LGBM,Stacked,0.95,0.985,1.898715517611114,0.33657448062658235,200
-rdflex,cutoff,Linear,Global linear,0.9,0.93,9.075817172665094,2.199047016932969,200
-rdflex,cutoff,Linear,Global linear,0.95,0.975,10.814503185710231,2.199047016932969,200
-rdflex,cutoff,Linear,LGBM,0.9,0.945,9.006421996493895,2.2499576335207867,200
-rdflex,cutoff,Linear,LGBM,0.95,0.975,10.731813733124445,2.2499576335207867,200
-rdflex,cutoff,Linear,Linear,0.9,0.93,9.19023631539689,2.2324898070695376,200
-rdflex,cutoff,Linear,Linear,0.95,0.975,10.95084200347598,2.2324898070695376,200
-rdflex,cutoff,Linear,Stacked,0.9,0.93,8.868858682952633,2.170604197519602,200
-rdflex,cutoff,Linear,Stacked,0.95,0.98,10.567896934865278,2.170604197519602,200
-rdflex,cutoff,Stacked,Global linear,0.9,0.94,1.7082355652914638,0.3858776284107599,200
-rdflex,cutoff,Stacked,Global linear,0.95,0.99,2.0354882223088335,0.3858776284107599,200
-rdflex,cutoff,Stacked,LGBM,0.9,0.95,1.6152877419864777,0.38023115554419357,200
-rdflex,cutoff,Stacked,LGBM,0.95,0.97,1.9247340596683542,0.38023115554419357,200
-rdflex,cutoff,Stacked,Linear,0.9,0.9,1.7085892928386948,0.38715972085633743,200
-rdflex,cutoff,Stacked,Linear,0.95,0.96,2.0359097146784597,0.38715972085633743,200
-rdflex,cutoff,Stacked,Stacked,0.9,0.955,1.6143624078750711,0.3399797304777219,200
-rdflex,cutoff,Stacked,Stacked,0.95,0.975,1.9236314560674583,0.3399797304777219,200
-rdflex,cutoff and score,Global linear,Global linear,0.9,0.945,9.080075892369969,2.1932099043718005,200
-rdflex,cutoff and score,Global linear,Global linear,0.95,0.97,10.819577763231928,2.1932099043718005,200
-rdflex,cutoff and score,Global linear,LGBM,0.9,0.955,9.123861848035432,2.26628855189193,200
-rdflex,cutoff and score,Global linear,LGBM,0.95,0.98,10.871751947443094,2.26628855189193,200
-rdflex,cutoff and score,Global linear,Linear,0.9,0.94,9.161670882012661,2.2100071846242657,200
-rdflex,cutoff and score,Global linear,Linear,0.95,0.97,10.916804190190655,2.2100071846242657,200
-rdflex,cutoff and score,Global linear,Stacked,0.9,0.945,9.12900517734864,2.234311195114868,200
-rdflex,cutoff and score,Global linear,Stacked,0.95,0.975,10.877880602327238,2.234311195114868,200
-rdflex,cutoff and score,LGBM,Global linear,0.9,0.975,1.7677213444582995,0.3895705364821883,200
-rdflex,cutoff and score,LGBM,Global linear,0.95,0.99,2.1063699000757397,0.3895705364821883,200
-rdflex,cutoff and score,LGBM,LGBM,0.9,0.955,1.7097986739938167,0.3989682200244538,200
-rdflex,cutoff and score,LGBM,LGBM,0.95,0.975,2.0373507812078957,0.3989682200244538,200
-rdflex,cutoff and score,LGBM,Linear,0.9,0.95,1.7436698369090557,0.3896899920948269,200
-rdflex,cutoff and score,LGBM,Linear,0.95,0.98,2.0777107611724324,0.3896899920948269,200
-rdflex,cutoff and score,LGBM,Stacked,0.9,0.945,1.6921819422814257,0.3976386225783639,200
-rdflex,cutoff and score,LGBM,Stacked,0.95,0.985,2.0163591506361316,0.3976386225783639,200
-rdflex,cutoff and score,Linear,Global linear,0.9,0.935,9.140994535035215,2.2292520538999314,200
-rdflex,cutoff and score,Linear,Global linear,0.95,0.975,10.892166803165066,2.2292520538999314,200
-rdflex,cutoff and score,Linear,LGBM,0.9,0.945,9.230547983693715,2.2907915601909408,200
-rdflex,cutoff and score,Linear,LGBM,0.95,0.98,10.9988763189457,2.2907915601909408,200
-rdflex,cutoff and score,Linear,Linear,0.9,0.925,9.159848674913668,2.2075015174066497,200
-rdflex,cutoff and score,Linear,Linear,0.95,0.975,10.914632896509636,2.2075015174066497,200
-rdflex,cutoff and score,Linear,Stacked,0.9,0.935,8.986928535062534,2.2429319842794295,200
-rdflex,cutoff and score,Linear,Stacked,0.95,0.975,10.708585841162837,2.2429319842794295,200
-rdflex,cutoff and score,Stacked,Global linear,0.9,0.91,1.776522112039948,0.39332706585160665,200
-rdflex,cutoff and score,Stacked,Global linear,0.95,0.97,2.1168566614590656,0.39332706585160665,200
-rdflex,cutoff and score,Stacked,LGBM,0.9,0.925,1.709515895023752,0.4026131018857037,200
-rdflex,cutoff and score,Stacked,LGBM,0.95,0.975,2.037013829282307,0.4026131018857037,200
-rdflex,cutoff and score,Stacked,Linear,0.9,0.945,1.7808563057254776,0.4007040458728064,200
-rdflex,cutoff and score,Stacked,Linear,0.95,0.995,2.122021171775648,0.4007040458728064,200
-rdflex,cutoff and score,Stacked,Stacked,0.9,0.925,1.74556578243726,0.39512341857753314,200
-rdflex,cutoff and score,Stacked,Stacked,0.95,0.98,2.0799699196112393,0.39512341857753314,200
-rdflex,interacted cutoff and score,Global linear,Global linear,0.9,0.93,9.061017454676579,2.180506418406957,200
-rdflex,interacted cutoff and score,Global linear,Global linear,0.95,0.975,10.796868234026052,2.180506418406957,200
-rdflex,interacted cutoff and score,Global linear,LGBM,0.9,0.945,9.191021529436847,2.2563449662547352,200
-rdflex,interacted cutoff and score,Global linear,LGBM,0.95,0.97,10.951777643713662,2.2563449662547352,200
-rdflex,interacted cutoff and score,Global linear,Linear,0.9,0.935,9.167705084002202,2.2186339606032286,200
-rdflex,interacted cutoff and score,Global linear,Linear,0.95,0.975,10.923994385343072,2.2186339606032286,200
-rdflex,interacted cutoff and score,Global linear,Stacked,0.9,0.955,8.984109518341889,2.215893099200206,200
-rdflex,interacted cutoff and score,Global linear,Stacked,0.95,0.975,10.705226775557394,2.215893099200206,200
-rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.95,1.78003628124215,0.40021895592964696,200
-rdflex,interacted cutoff and score,LGBM,Global linear,0.95,0.985,2.121044052336308,0.40021895592964696,200
-rdflex,interacted cutoff and score,LGBM,LGBM,0.9,0.945,1.7352078615081552,0.3682890431886914,200
-rdflex,interacted cutoff and score,LGBM,LGBM,0.95,0.98,2.0676276955718977,0.3682890431886914,200
-rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.94,1.7626227479121315,0.38482868938106907,200
-rdflex,interacted cutoff and score,LGBM,Linear,0.95,0.985,2.1002945475711456,0.38482868938106907,200
-rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.93,1.7237010890318276,0.4070129098798606,200
-rdflex,interacted cutoff and score,LGBM,Stacked,0.95,0.99,2.0539165304795377,0.4070129098798606,200
-rdflex,interacted cutoff and score,Linear,Global linear,0.9,0.93,9.196222925824271,2.2332568020997727,200
-rdflex,interacted cutoff and score,Linear,Global linear,0.95,0.975,10.957975489784355,2.2332568020997727,200
-rdflex,interacted cutoff and score,Linear,LGBM,0.9,0.945,9.261389340916475,2.2694537643554695,200
-rdflex,interacted cutoff and score,Linear,LGBM,0.95,0.97,11.035626062752984,2.2694537643554695,200
-rdflex,interacted cutoff and score,Linear,Linear,0.9,0.93,9.263515375167458,2.2377624722965814,200
-rdflex,interacted cutoff and score,Linear,Linear,0.95,0.975,11.038159388815284,2.2377624722965814,200
-rdflex,interacted cutoff and score,Linear,Stacked,0.9,0.95,9.123427141504681,2.266717454845839,200
-rdflex,interacted cutoff and score,Linear,Stacked,0.95,0.975,10.87123396266308,2.266717454845839,200
-rdflex,interacted cutoff and score,Stacked,Global linear,0.9,0.955,1.81336839938933,0.38591136894636113,200
-rdflex,interacted cutoff and score,Stacked,Global linear,0.95,0.97,2.1607617208427676,0.38591136894636113,200
-rdflex,interacted cutoff and score,Stacked,LGBM,0.9,0.935,1.7411337194500436,0.3926129635572617,200
-rdflex,interacted cutoff and score,Stacked,LGBM,0.95,0.97,2.0746887908288216,0.3926129635572617,200
-rdflex,interacted cutoff and score,Stacked,Linear,0.9,0.935,1.8383865669851245,0.39956163215234425,200
-rdflex,interacted cutoff and score,Stacked,Linear,0.95,0.965,2.190572706235933,0.39956163215234425,200
-rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.935,1.772193337511724,0.38945684216992094,200
-rdflex,interacted cutoff and score,Stacked,Stacked,0.95,0.985,2.1116986084666918,0.38945684216992094,200
-rdrobust,cutoff,linear,linear,0.9,0.935,10.477786198433689,2.22067665589711,200
-rdrobust,cutoff,linear,linear,0.95,0.97,12.485052317209465,2.22067665589711,200
+rdflex,cutoff,Global linear,Global linear,0.9,0.94,10.656647912232243,2.633619695891854,200
+rdflex,cutoff,Global linear,Global linear,0.95,0.975,12.698179194588825,2.633619695891854,200
+rdflex,cutoff,Global linear,LGBM,0.9,0.95,10.643973412823318,2.683167754539693,200
+rdflex,cutoff,Global linear,LGBM,0.95,0.985,12.683076597034534,2.683167754539693,200
+rdflex,cutoff,Global linear,Linear,0.9,0.93,10.776049843790432,2.6771187550632725,200
+rdflex,cutoff,Global linear,Linear,0.95,0.975,12.840455371449803,2.6771187550632725,200
+rdflex,cutoff,Global linear,Stacked,0.9,0.94,10.557664798352551,2.683307036256171,200
+rdflex,cutoff,Global linear,Stacked,0.95,0.97,12.5802335396667,2.683307036256171,200
+rdflex,cutoff,LGBM,Global linear,0.9,0.93,1.9736186033277963,0.4736792492584584,200
+rdflex,cutoff,LGBM,Global linear,0.95,0.98,2.351711616376457,0.4736792492584584,200
+rdflex,cutoff,LGBM,LGBM,0.9,0.945,1.888140568372329,0.4540535620095493,200
+rdflex,cutoff,LGBM,LGBM,0.95,0.98,2.249858255544299,0.4540535620095493,200
+rdflex,cutoff,LGBM,Linear,0.9,0.94,1.9844665729368185,0.46134915372559027,200
+rdflex,cutoff,LGBM,Linear,0.95,0.99,2.364637769433902,0.46134915372559027,200
+rdflex,cutoff,LGBM,Stacked,0.9,0.94,1.8620008207876455,0.4012145704533858,200
+rdflex,cutoff,LGBM,Stacked,0.95,0.98,2.2187108251641856,0.4012145704533858,200
+rdflex,cutoff,Linear,Global linear,0.9,0.94,10.647635639786058,2.6416807260382247,200
+rdflex,cutoff,Linear,Global linear,0.95,0.975,12.687440409614917,2.6416807260382247,200
+rdflex,cutoff,Linear,LGBM,0.9,0.925,10.575702513090668,2.6809206077686394,200
+rdflex,cutoff,Linear,LGBM,0.95,0.975,12.60172680245364,2.6809206077686394,200
+rdflex,cutoff,Linear,Linear,0.9,0.93,10.779409511322877,2.6887526751987267,200
+rdflex,cutoff,Linear,Linear,0.95,0.975,12.844458662232476,2.6887526751987267,200
+rdflex,cutoff,Linear,Stacked,0.9,0.93,10.407357842739176,2.580058349572135,200
+rdflex,cutoff,Linear,Stacked,0.95,0.975,12.401131755288432,2.580058349572135,200
+rdflex,cutoff,Stacked,Global linear,0.9,0.93,1.9911373354406925,0.4571509115231827,200
+rdflex,cutoff,Stacked,Global linear,0.95,0.98,2.372586473222971,0.4571509115231827,200
+rdflex,cutoff,Stacked,LGBM,0.9,0.93,1.8837567274958633,0.44740832605498343,200
+rdflex,cutoff,Stacked,LGBM,0.95,0.98,2.2446345869509106,0.44740832605498343,200
+rdflex,cutoff,Stacked,Linear,0.9,0.9,1.989471103819308,0.45510016867576153,200
+rdflex,cutoff,Stacked,Linear,0.95,0.95,2.3706010357868945,0.45510016867576153,200
+rdflex,cutoff,Stacked,Stacked,0.9,0.96,1.8789097307697546,0.3941306179463427,200
+rdflex,cutoff,Stacked,Stacked,0.95,0.975,2.2388590341231716,0.3941306179463427,200
+rdflex,cutoff and score,Global linear,Global linear,0.9,0.94,10.650117280929118,2.6412998313409854,200
+rdflex,cutoff and score,Global linear,Global linear,0.95,0.975,12.69039746742435,2.6412998313409854,200
+rdflex,cutoff and score,Global linear,LGBM,0.9,0.945,10.73149277430906,2.71273519074909,200
+rdflex,cutoff and score,Global linear,LGBM,0.95,0.975,12.7873623484542,2.71273519074909,200
+rdflex,cutoff and score,Global linear,Linear,0.9,0.935,10.749492570130274,2.6660832359136544,200
+rdflex,cutoff and score,Global linear,Linear,0.95,0.975,12.808810428064808,2.6660832359136544,200
+rdflex,cutoff and score,Global linear,Stacked,0.9,0.935,10.73720670502136,2.6787331039175375,200
+rdflex,cutoff and score,Global linear,Stacked,0.95,0.97,12.794170916841543,2.6787331039175375,200
+rdflex,cutoff and score,LGBM,Global linear,0.9,0.965,2.047945503750196,0.45373290004575745,200
+rdflex,cutoff and score,LGBM,Global linear,0.95,0.99,2.4402775808631536,0.45373290004575745,200
+rdflex,cutoff and score,LGBM,LGBM,0.9,0.96,1.9815030650940242,0.47287637385657555,200
+rdflex,cutoff and score,LGBM,LGBM,0.95,0.985,2.3611065320370863,0.47287637385657555,200
+rdflex,cutoff and score,LGBM,Linear,0.9,0.95,2.0210088746612995,0.4564734865636682,200
+rdflex,cutoff and score,LGBM,Linear,0.95,0.985,2.408180607604202,0.4564734865636682,200
+rdflex,cutoff and score,LGBM,Stacked,0.9,0.96,1.9571852817725235,0.4704140225228424,200
+rdflex,cutoff and score,LGBM,Stacked,0.95,0.98,2.3321301059812765,0.4704140225228424,200
+rdflex,cutoff and score,Linear,Global linear,0.9,0.935,10.72114800697828,2.677543618743263,200
+rdflex,cutoff and score,Linear,Global linear,0.95,0.975,12.775035797893981,2.677543618743263,200
+rdflex,cutoff and score,Linear,LGBM,0.9,0.93,10.860224829406206,2.7531128907921176,200
+rdflex,cutoff and score,Linear,LGBM,0.95,0.98,12.940756053226494,2.7531128907921176,200
+rdflex,cutoff and score,Linear,Linear,0.9,0.93,10.745408698465134,2.661897345725493,200
+rdflex,cutoff and score,Linear,Linear,0.95,0.975,12.803944194832864,2.661897345725493,200
+rdflex,cutoff and score,Linear,Stacked,0.9,0.93,10.559755783592582,2.673709652399862,200
+rdflex,cutoff and score,Linear,Stacked,0.95,0.97,12.58272510225654,2.673709652399862,200
+rdflex,cutoff and score,Stacked,Global linear,0.9,0.9,2.050300073797309,0.462407370604782,200
+rdflex,cutoff and score,Stacked,Global linear,0.95,0.965,2.4430832241227134,0.462407370604782,200
+rdflex,cutoff and score,Stacked,LGBM,0.9,0.94,1.9791092813189477,0.46255297446802196,200
+rdflex,cutoff and score,Stacked,LGBM,0.95,0.98,2.3582541627386573,0.46255297446802196,200
+rdflex,cutoff and score,Stacked,Linear,0.9,0.96,2.053260325247618,0.4749983725128283,200
+rdflex,cutoff and score,Stacked,Linear,0.95,0.995,2.446610581288555,0.4749983725128283,200
+rdflex,cutoff and score,Stacked,Stacked,0.9,0.945,2.0147063198301267,0.46298147786251936,200
+rdflex,cutoff and score,Stacked,Stacked,0.95,0.975,2.400670650318469,0.46298147786251936,200
+rdflex,interacted cutoff and score,Global linear,Global linear,0.9,0.94,10.631418110341247,2.6178877718072253,200
+rdflex,interacted cutoff and score,Global linear,Global linear,0.95,0.975,12.66811603137893,2.6178877718072253,200
+rdflex,interacted cutoff and score,Global linear,LGBM,0.9,0.955,10.814413902878202,2.6873104399748953,200
+rdflex,interacted cutoff and score,Global linear,LGBM,0.95,0.975,12.886168967407977,2.6873104399748953,200
+rdflex,interacted cutoff and score,Global linear,Linear,0.9,0.945,10.740747890043254,2.6612642120114547,200
+rdflex,interacted cutoff and score,Global linear,Linear,0.95,0.975,12.798390499053465,2.6612642120114547,200
+rdflex,interacted cutoff and score,Global linear,Stacked,0.9,0.945,10.571286636735614,2.648449325171482,200
+rdflex,interacted cutoff and score,Global linear,Stacked,0.95,0.97,12.596464961233078,2.648449325171482,200
+rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.94,2.0617998183606496,0.4778778382609598,200
+rdflex,interacted cutoff and score,LGBM,Global linear,0.95,0.995,2.4567860149402345,0.4778778382609598,200
+rdflex,interacted cutoff and score,LGBM,LGBM,0.9,0.955,2.011772406234098,0.4375432216964436,200
+rdflex,interacted cutoff and score,LGBM,LGBM,0.95,0.99,2.3971746766416953,0.4375432216964436,200
+rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.925,2.043336186918838,0.45592138226951223,200
+rdflex,interacted cutoff and score,LGBM,Linear,0.95,0.985,2.434785241098223,0.45592138226951223,200
+rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.92,1.9999285735150907,0.4849897427944731,200
+rdflex,interacted cutoff and score,LGBM,Stacked,0.95,0.99,2.3830618794980403,0.4849897427944731,200
+rdflex,interacted cutoff and score,Linear,Global linear,0.9,0.93,10.776821610680779,2.6847245127079207,200
+rdflex,interacted cutoff and score,Linear,Global linear,0.95,0.975,12.84137498842043,2.6847245127079207,200
+rdflex,interacted cutoff and score,Linear,LGBM,0.9,0.93,10.885600365474607,2.7261863873540197,200
+rdflex,interacted cutoff and score,Linear,LGBM,0.95,0.975,12.970992869419458,2.7261863873540197,200
+rdflex,interacted cutoff and score,Linear,Linear,0.9,0.945,10.848347906235588,2.6866349482211676,200
+rdflex,interacted cutoff and score,Linear,Linear,0.95,0.975,12.92660382637777,2.6866349482211676,200
+rdflex,interacted cutoff and score,Linear,Stacked,0.9,0.935,10.718031056371272,2.710115186333965,200
+rdflex,interacted cutoff and score,Linear,Stacked,0.95,0.97,12.771321722166373,2.710115186333965,200
+rdflex,interacted cutoff and score,Stacked,Global linear,0.9,0.955,2.0898744689631377,0.4446184515603455,200
+rdflex,interacted cutoff and score,Stacked,Global linear,0.95,0.975,2.4902390244711827,0.4446184515603455,200
+rdflex,interacted cutoff and score,Stacked,LGBM,0.9,0.945,2.009366557570152,0.46359739512200543,200
+rdflex,interacted cutoff and score,Stacked,LGBM,0.95,0.98,2.3943079311414723,0.46359739512200543,200
+rdflex,interacted cutoff and score,Stacked,Linear,0.9,0.925,2.109705996199304,0.4783528357695981,200
+rdflex,interacted cutoff and score,Stacked,Linear,0.95,0.975,2.5138697466852618,0.4783528357695981,200
+rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.93,2.0357591930356382,0.4580324320952215,200
+rdflex,interacted cutoff and score,Stacked,Stacked,0.95,0.99,2.4257566960174817,0.4580324320952215,200
+rdrobust,cutoff,linear,linear,0.9,0.935,10.477786198433689,2.6328998952957328,200
+rdrobust,cutoff,linear,linear,0.95,0.97,12.485052317209465,2.6328998952957328,200
diff --git a/results/rdd/rdd_fuzzy_coverage_metadata.csv b/results/rdd/rdd_fuzzy_coverage_metadata.csv
index a19ddd2..c088ee5 100644
--- a/results/rdd/rdd_fuzzy_coverage_metadata.csv
+++ b/results/rdd/rdd_fuzzy_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_fuzzy_coverage.py,2024-10-14 11:56:14,12188.346573114395,3.12.7
+0.9.dev0,rdd_fuzzy_coverage.py,2024-10-15 12:05:47,11919.275193691254,3.12.7

From 38bd36d976a5792ff8e929c331f21389535a5f22 Mon Sep 17 00:00:00 2001
From: Sven Klaassen <47529404+SvenKlaassen@users.noreply.github.com>
Date: Mon, 21 Oct 2024 16:02:59 +0200
Subject: [PATCH 22/58] increase repetitions

---
 scripts/rdd/rdd_fuzzy_coverage.py | 2 +-
 scripts/rdd/rdd_sharp_coverage.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/scripts/rdd/rdd_fuzzy_coverage.py b/scripts/rdd/rdd_fuzzy_coverage.py
index 5ec5491..f9773fa 100644
--- a/scripts/rdd/rdd_fuzzy_coverage.py
+++ b/scripts/rdd/rdd_fuzzy_coverage.py
@@ -18,7 +18,7 @@
 
 
 # Number of repetitions
-n_rep = 200
+n_rep = 500
 max_runtime = 5.5 * 3600  # 5.5 hours in seconds
 
 # DGP pars
diff --git a/scripts/rdd/rdd_sharp_coverage.py b/scripts/rdd/rdd_sharp_coverage.py
index 30d5d95..bff96f9 100644
--- a/scripts/rdd/rdd_sharp_coverage.py
+++ b/scripts/rdd/rdd_sharp_coverage.py
@@ -18,7 +18,7 @@
 
 
 # Number of repetitions
-n_rep = 200
+n_rep = 500
 max_runtime = 5.5 * 3600  # 5.5 hours in seconds
 
 # DGP pars

From 8403e80b173009a8658c953c4c02587cec381890 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Mon, 21 Oct 2024 15:13:56 +0000
Subject: [PATCH 23/58] Update results from script:
 scripts/rdd/rdd_sharp_coverage.py

---
 results/rdd/rdd_sharp_coverage.csv          | 52 ++++++++++-----------
 results/rdd/rdd_sharp_coverage_metadata.csv |  2 +-
 2 files changed, 27 insertions(+), 27 deletions(-)

diff --git a/results/rdd/rdd_sharp_coverage.csv b/results/rdd/rdd_sharp_coverage.csv
index c7c123f..558f06e 100644
--- a/results/rdd/rdd_sharp_coverage.csv
+++ b/results/rdd/rdd_sharp_coverage.csv
@@ -1,27 +1,27 @@
 Method,fs specification,Learner g,level,Coverage,CI Length,Bias,repetition
-rdflex,cutoff,Global linear,0.9,0.85,2.2038817328826754,0.5781853469884299,200
-rdflex,cutoff,Global linear,0.95,0.895,2.626087058361215,0.5781853469884299,200
-rdflex,cutoff,LGBM,0.9,0.9,0.5489293795795934,0.14138881305826245,200
-rdflex,cutoff,LGBM,0.95,0.94,0.654089699170333,0.14138881305826245,200
-rdflex,cutoff,Linear,0.9,0.85,2.212426058297747,0.5869505014882239,200
-rdflex,cutoff,Linear,0.95,0.9,2.6362682500559247,0.5869505014882239,200
-rdflex,cutoff,Stacked,0.9,0.89,0.5401104795583865,0.13671196195207622,200
-rdflex,cutoff,Stacked,0.95,0.935,0.6435813316526349,0.13671196195207622,200
-rdflex,cutoff and score,Global linear,0.9,0.855,2.2031794642927314,0.5803760017012753,200
-rdflex,cutoff and score,Global linear,0.95,0.9,2.625250253723276,0.5803760017012753,200
-rdflex,cutoff and score,LGBM,0.9,0.91,0.5661903205762662,0.14041644950018034,200
-rdflex,cutoff and score,LGBM,0.95,0.95,0.6746573789555858,0.14041644950018034,200
-rdflex,cutoff and score,Linear,0.9,0.85,2.210257349249581,0.5861956425526764,200
-rdflex,cutoff and score,Linear,0.95,0.9,2.63368407383641,0.5861956425526764,200
-rdflex,cutoff and score,Stacked,0.9,0.865,0.5526668555917932,0.15053840369931945,200
-rdflex,cutoff and score,Stacked,0.95,0.91,0.6585431765235554,0.15053840369931945,200
-rdflex,interacted cutoff and score,Global linear,0.9,0.855,2.2067448709410886,0.5796586405457141,200
-rdflex,interacted cutoff and score,Global linear,0.95,0.9,2.6294986977832933,0.5796586405457141,200
-rdflex,interacted cutoff and score,LGBM,0.9,0.87,0.5675129418312119,0.1515231799200044,200
-rdflex,interacted cutoff and score,LGBM,0.95,0.92,0.676233379386509,0.1515231799200044,200
-rdflex,interacted cutoff and score,Linear,0.9,0.855,2.2209084131452888,0.5832381244405058,200
-rdflex,interacted cutoff and score,Linear,0.95,0.895,2.6463755992649136,0.5832381244405058,200
-rdflex,interacted cutoff and score,Stacked,0.9,0.84,0.5635026024806519,0.1540631695077759,200
-rdflex,interacted cutoff and score,Stacked,0.95,0.93,0.6714547653116205,0.1540631695077759,200
-rdrobust,cutoff,linear,0.9,0.84,2.184383574713776,0.585928851003536,200
-rdrobust,cutoff,linear,0.95,0.895,2.602853569891644,0.585928851003536,200
+rdflex,cutoff,Global linear,0.9,0.874,2.2011088216647567,0.5534513823633507,500
+rdflex,cutoff,Global linear,0.95,0.922,2.6227829308507813,0.5534513823633507,500
+rdflex,cutoff,LGBM,0.9,0.914,0.5720094363002372,0.1386055523323647,500
+rdflex,cutoff,LGBM,0.95,0.96,0.681591283014874,0.1386055523323647,500
+rdflex,cutoff,Linear,0.9,0.874,2.2135060296971463,0.558126057195101,500
+rdflex,cutoff,Linear,0.95,0.918,2.6375551153504855,0.558126057195101,500
+rdflex,cutoff,Stacked,0.9,0.9,0.5590842827226126,0.12977180379581715,500
+rdflex,cutoff,Stacked,0.95,0.964,0.6661900125968221,0.12977180379581715,500
+rdflex,cutoff and score,Global linear,0.9,0.876,2.2005650015589864,0.5551812535814453,500
+rdflex,cutoff and score,Global linear,0.95,0.922,2.622134929226859,0.5551812535814453,500
+rdflex,cutoff and score,LGBM,0.9,0.902,0.5984294788353389,0.14476299319184177,500
+rdflex,cutoff and score,LGBM,0.95,0.95,0.7130727054286046,0.14476299319184177,500
+rdflex,cutoff and score,Linear,0.9,0.87,2.212887444081595,0.5582781571131341,500
+rdflex,cutoff and score,Linear,0.95,0.922,2.63681802512679,0.5582781571131341,500
+rdflex,cutoff and score,Stacked,0.9,0.88,0.5820101876494705,0.14231610717047102,500
+rdflex,cutoff and score,Stacked,0.95,0.956,0.6935079132497274,0.14231610717047102,500
+rdflex,interacted cutoff and score,Global linear,0.9,0.878,2.202268208292408,0.5546663773642981,500
+rdflex,interacted cutoff and score,Global linear,0.95,0.926,2.6241644252264025,0.5546663773642981,500
+rdflex,interacted cutoff and score,LGBM,0.9,0.886,0.6002731299225453,0.151487055237104,500
+rdflex,interacted cutoff and score,LGBM,0.95,0.948,0.7152695511975984,0.151487055237104,500
+rdflex,interacted cutoff and score,Linear,0.9,0.88,2.2252512728137637,0.5541600195953326,500
+rdflex,interacted cutoff and score,Linear,0.95,0.916,2.651550435737079,0.5541600195953326,500
+rdflex,interacted cutoff and score,Stacked,0.9,0.904,0.5793073094025809,0.14171607962579613,500
+rdflex,interacted cutoff and score,Stacked,0.95,0.962,0.6902872351713266,0.14171607962579613,500
+rdrobust,cutoff,linear,0.9,0.874,2.1797037623552287,0.555486091306879,500
+rdrobust,cutoff,linear,0.95,0.916,2.597277229525019,0.555486091306879,500
diff --git a/results/rdd/rdd_sharp_coverage_metadata.csv b/results/rdd/rdd_sharp_coverage_metadata.csv
index 9815438..8fe5f1b 100644
--- a/results/rdd/rdd_sharp_coverage_metadata.csv
+++ b/results/rdd/rdd_sharp_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_sharp_coverage.py,2024-10-15 09:14:30,1643.302789926529,3.12.7
+0.9.dev0,rdd_sharp_coverage.py,2024-10-21 15:13:55,4153.726145505905,3.12.7

From 5c603b2a69ecd8060dd5e0203fa97b1986378817 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Mon, 21 Oct 2024 19:35:10 +0000
Subject: [PATCH 24/58] Update results from script:
 scripts/rdd/rdd_fuzzy_coverage.py

---
 results/rdd/rdd_fuzzy_coverage.csv          | 196 ++++++++++----------
 results/rdd/rdd_fuzzy_coverage_metadata.csv |   2 +-
 2 files changed, 99 insertions(+), 99 deletions(-)

diff --git a/results/rdd/rdd_fuzzy_coverage.csv b/results/rdd/rdd_fuzzy_coverage.csv
index b9643bf..5497bfd 100644
--- a/results/rdd/rdd_fuzzy_coverage.csv
+++ b/results/rdd/rdd_fuzzy_coverage.csv
@@ -1,99 +1,99 @@
 Method,fs specification,Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-rdflex,cutoff,Global linear,Global linear,0.9,0.94,10.656647912232243,2.633619695891854,200
-rdflex,cutoff,Global linear,Global linear,0.95,0.975,12.698179194588825,2.633619695891854,200
-rdflex,cutoff,Global linear,LGBM,0.9,0.95,10.643973412823318,2.683167754539693,200
-rdflex,cutoff,Global linear,LGBM,0.95,0.985,12.683076597034534,2.683167754539693,200
-rdflex,cutoff,Global linear,Linear,0.9,0.93,10.776049843790432,2.6771187550632725,200
-rdflex,cutoff,Global linear,Linear,0.95,0.975,12.840455371449803,2.6771187550632725,200
-rdflex,cutoff,Global linear,Stacked,0.9,0.94,10.557664798352551,2.683307036256171,200
-rdflex,cutoff,Global linear,Stacked,0.95,0.97,12.5802335396667,2.683307036256171,200
-rdflex,cutoff,LGBM,Global linear,0.9,0.93,1.9736186033277963,0.4736792492584584,200
-rdflex,cutoff,LGBM,Global linear,0.95,0.98,2.351711616376457,0.4736792492584584,200
-rdflex,cutoff,LGBM,LGBM,0.9,0.945,1.888140568372329,0.4540535620095493,200
-rdflex,cutoff,LGBM,LGBM,0.95,0.98,2.249858255544299,0.4540535620095493,200
-rdflex,cutoff,LGBM,Linear,0.9,0.94,1.9844665729368185,0.46134915372559027,200
-rdflex,cutoff,LGBM,Linear,0.95,0.99,2.364637769433902,0.46134915372559027,200
-rdflex,cutoff,LGBM,Stacked,0.9,0.94,1.8620008207876455,0.4012145704533858,200
-rdflex,cutoff,LGBM,Stacked,0.95,0.98,2.2187108251641856,0.4012145704533858,200
-rdflex,cutoff,Linear,Global linear,0.9,0.94,10.647635639786058,2.6416807260382247,200
-rdflex,cutoff,Linear,Global linear,0.95,0.975,12.687440409614917,2.6416807260382247,200
-rdflex,cutoff,Linear,LGBM,0.9,0.925,10.575702513090668,2.6809206077686394,200
-rdflex,cutoff,Linear,LGBM,0.95,0.975,12.60172680245364,2.6809206077686394,200
-rdflex,cutoff,Linear,Linear,0.9,0.93,10.779409511322877,2.6887526751987267,200
-rdflex,cutoff,Linear,Linear,0.95,0.975,12.844458662232476,2.6887526751987267,200
-rdflex,cutoff,Linear,Stacked,0.9,0.93,10.407357842739176,2.580058349572135,200
-rdflex,cutoff,Linear,Stacked,0.95,0.975,12.401131755288432,2.580058349572135,200
-rdflex,cutoff,Stacked,Global linear,0.9,0.93,1.9911373354406925,0.4571509115231827,200
-rdflex,cutoff,Stacked,Global linear,0.95,0.98,2.372586473222971,0.4571509115231827,200
-rdflex,cutoff,Stacked,LGBM,0.9,0.93,1.8837567274958633,0.44740832605498343,200
-rdflex,cutoff,Stacked,LGBM,0.95,0.98,2.2446345869509106,0.44740832605498343,200
-rdflex,cutoff,Stacked,Linear,0.9,0.9,1.989471103819308,0.45510016867576153,200
-rdflex,cutoff,Stacked,Linear,0.95,0.95,2.3706010357868945,0.45510016867576153,200
-rdflex,cutoff,Stacked,Stacked,0.9,0.96,1.8789097307697546,0.3941306179463427,200
-rdflex,cutoff,Stacked,Stacked,0.95,0.975,2.2388590341231716,0.3941306179463427,200
-rdflex,cutoff and score,Global linear,Global linear,0.9,0.94,10.650117280929118,2.6412998313409854,200
-rdflex,cutoff and score,Global linear,Global linear,0.95,0.975,12.69039746742435,2.6412998313409854,200
-rdflex,cutoff and score,Global linear,LGBM,0.9,0.945,10.73149277430906,2.71273519074909,200
-rdflex,cutoff and score,Global linear,LGBM,0.95,0.975,12.7873623484542,2.71273519074909,200
-rdflex,cutoff and score,Global linear,Linear,0.9,0.935,10.749492570130274,2.6660832359136544,200
-rdflex,cutoff and score,Global linear,Linear,0.95,0.975,12.808810428064808,2.6660832359136544,200
-rdflex,cutoff and score,Global linear,Stacked,0.9,0.935,10.73720670502136,2.6787331039175375,200
-rdflex,cutoff and score,Global linear,Stacked,0.95,0.97,12.794170916841543,2.6787331039175375,200
-rdflex,cutoff and score,LGBM,Global linear,0.9,0.965,2.047945503750196,0.45373290004575745,200
-rdflex,cutoff and score,LGBM,Global linear,0.95,0.99,2.4402775808631536,0.45373290004575745,200
-rdflex,cutoff and score,LGBM,LGBM,0.9,0.96,1.9815030650940242,0.47287637385657555,200
-rdflex,cutoff and score,LGBM,LGBM,0.95,0.985,2.3611065320370863,0.47287637385657555,200
-rdflex,cutoff and score,LGBM,Linear,0.9,0.95,2.0210088746612995,0.4564734865636682,200
-rdflex,cutoff and score,LGBM,Linear,0.95,0.985,2.408180607604202,0.4564734865636682,200
-rdflex,cutoff and score,LGBM,Stacked,0.9,0.96,1.9571852817725235,0.4704140225228424,200
-rdflex,cutoff and score,LGBM,Stacked,0.95,0.98,2.3321301059812765,0.4704140225228424,200
-rdflex,cutoff and score,Linear,Global linear,0.9,0.935,10.72114800697828,2.677543618743263,200
-rdflex,cutoff and score,Linear,Global linear,0.95,0.975,12.775035797893981,2.677543618743263,200
-rdflex,cutoff and score,Linear,LGBM,0.9,0.93,10.860224829406206,2.7531128907921176,200
-rdflex,cutoff and score,Linear,LGBM,0.95,0.98,12.940756053226494,2.7531128907921176,200
-rdflex,cutoff and score,Linear,Linear,0.9,0.93,10.745408698465134,2.661897345725493,200
-rdflex,cutoff and score,Linear,Linear,0.95,0.975,12.803944194832864,2.661897345725493,200
-rdflex,cutoff and score,Linear,Stacked,0.9,0.93,10.559755783592582,2.673709652399862,200
-rdflex,cutoff and score,Linear,Stacked,0.95,0.97,12.58272510225654,2.673709652399862,200
-rdflex,cutoff and score,Stacked,Global linear,0.9,0.9,2.050300073797309,0.462407370604782,200
-rdflex,cutoff and score,Stacked,Global linear,0.95,0.965,2.4430832241227134,0.462407370604782,200
-rdflex,cutoff and score,Stacked,LGBM,0.9,0.94,1.9791092813189477,0.46255297446802196,200
-rdflex,cutoff and score,Stacked,LGBM,0.95,0.98,2.3582541627386573,0.46255297446802196,200
-rdflex,cutoff and score,Stacked,Linear,0.9,0.96,2.053260325247618,0.4749983725128283,200
-rdflex,cutoff and score,Stacked,Linear,0.95,0.995,2.446610581288555,0.4749983725128283,200
-rdflex,cutoff and score,Stacked,Stacked,0.9,0.945,2.0147063198301267,0.46298147786251936,200
-rdflex,cutoff and score,Stacked,Stacked,0.95,0.975,2.400670650318469,0.46298147786251936,200
-rdflex,interacted cutoff and score,Global linear,Global linear,0.9,0.94,10.631418110341247,2.6178877718072253,200
-rdflex,interacted cutoff and score,Global linear,Global linear,0.95,0.975,12.66811603137893,2.6178877718072253,200
-rdflex,interacted cutoff and score,Global linear,LGBM,0.9,0.955,10.814413902878202,2.6873104399748953,200
-rdflex,interacted cutoff and score,Global linear,LGBM,0.95,0.975,12.886168967407977,2.6873104399748953,200
-rdflex,interacted cutoff and score,Global linear,Linear,0.9,0.945,10.740747890043254,2.6612642120114547,200
-rdflex,interacted cutoff and score,Global linear,Linear,0.95,0.975,12.798390499053465,2.6612642120114547,200
-rdflex,interacted cutoff and score,Global linear,Stacked,0.9,0.945,10.571286636735614,2.648449325171482,200
-rdflex,interacted cutoff and score,Global linear,Stacked,0.95,0.97,12.596464961233078,2.648449325171482,200
-rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.94,2.0617998183606496,0.4778778382609598,200
-rdflex,interacted cutoff and score,LGBM,Global linear,0.95,0.995,2.4567860149402345,0.4778778382609598,200
-rdflex,interacted cutoff and score,LGBM,LGBM,0.9,0.955,2.011772406234098,0.4375432216964436,200
-rdflex,interacted cutoff and score,LGBM,LGBM,0.95,0.99,2.3971746766416953,0.4375432216964436,200
-rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.925,2.043336186918838,0.45592138226951223,200
-rdflex,interacted cutoff and score,LGBM,Linear,0.95,0.985,2.434785241098223,0.45592138226951223,200
-rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.92,1.9999285735150907,0.4849897427944731,200
-rdflex,interacted cutoff and score,LGBM,Stacked,0.95,0.99,2.3830618794980403,0.4849897427944731,200
-rdflex,interacted cutoff and score,Linear,Global linear,0.9,0.93,10.776821610680779,2.6847245127079207,200
-rdflex,interacted cutoff and score,Linear,Global linear,0.95,0.975,12.84137498842043,2.6847245127079207,200
-rdflex,interacted cutoff and score,Linear,LGBM,0.9,0.93,10.885600365474607,2.7261863873540197,200
-rdflex,interacted cutoff and score,Linear,LGBM,0.95,0.975,12.970992869419458,2.7261863873540197,200
-rdflex,interacted cutoff and score,Linear,Linear,0.9,0.945,10.848347906235588,2.6866349482211676,200
-rdflex,interacted cutoff and score,Linear,Linear,0.95,0.975,12.92660382637777,2.6866349482211676,200
-rdflex,interacted cutoff and score,Linear,Stacked,0.9,0.935,10.718031056371272,2.710115186333965,200
-rdflex,interacted cutoff and score,Linear,Stacked,0.95,0.97,12.771321722166373,2.710115186333965,200
-rdflex,interacted cutoff and score,Stacked,Global linear,0.9,0.955,2.0898744689631377,0.4446184515603455,200
-rdflex,interacted cutoff and score,Stacked,Global linear,0.95,0.975,2.4902390244711827,0.4446184515603455,200
-rdflex,interacted cutoff and score,Stacked,LGBM,0.9,0.945,2.009366557570152,0.46359739512200543,200
-rdflex,interacted cutoff and score,Stacked,LGBM,0.95,0.98,2.3943079311414723,0.46359739512200543,200
-rdflex,interacted cutoff and score,Stacked,Linear,0.9,0.925,2.109705996199304,0.4783528357695981,200
-rdflex,interacted cutoff and score,Stacked,Linear,0.95,0.975,2.5138697466852618,0.4783528357695981,200
-rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.93,2.0357591930356382,0.4580324320952215,200
-rdflex,interacted cutoff and score,Stacked,Stacked,0.95,0.99,2.4257566960174817,0.4580324320952215,200
-rdrobust,cutoff,linear,linear,0.9,0.935,10.477786198433689,2.6328998952957328,200
-rdrobust,cutoff,linear,linear,0.95,0.97,12.485052317209465,2.6328998952957328,200
+rdflex,cutoff,Global linear,Global linear,0.9,0.9294478527607362,11.003281519552571,2.651668091366742,326
+rdflex,cutoff,Global linear,Global linear,0.95,0.9662576687116564,13.111218613444718,2.651668091366742,326
+rdflex,cutoff,Global linear,LGBM,0.9,0.9263803680981595,11.026796633476012,2.676212872142164,326
+rdflex,cutoff,Global linear,LGBM,0.95,0.9723926380368099,13.139238599920793,2.676212872142164,326
+rdflex,cutoff,Global linear,Linear,0.9,0.9263803680981595,11.061928208835385,2.6694105241913504,326
+rdflex,cutoff,Global linear,Linear,0.95,0.9662576687116564,13.181100453946152,2.6694105241913504,326
+rdflex,cutoff,Global linear,Stacked,0.9,0.9263803680981595,10.75270381540699,2.660157382556207,326
+rdflex,cutoff,Global linear,Stacked,0.95,0.9631901840490797,12.812636862821531,2.660157382556207,326
+rdflex,cutoff,LGBM,Global linear,0.9,0.9355828220858896,2.1367788053015517,0.48144779191064846,326
+rdflex,cutoff,LGBM,Global linear,0.95,0.9662576687116564,2.5461289884386313,0.48144779191064846,326
+rdflex,cutoff,LGBM,LGBM,0.9,0.941717791411043,2.118982251356838,0.49791701276459366,326
+rdflex,cutoff,LGBM,LGBM,0.95,0.9815950920245399,2.524923086461073,0.49791701276459366,326
+rdflex,cutoff,LGBM,Linear,0.9,0.9539877300613497,2.1750418199492105,0.4820841235532899,326
+rdflex,cutoff,LGBM,Linear,0.95,0.99079754601227,2.5917221825201815,0.4820841235532899,326
+rdflex,cutoff,LGBM,Stacked,0.9,0.9202453987730062,2.086735539677055,0.4797826433300534,326
+rdflex,cutoff,LGBM,Stacked,0.95,0.9723926380368099,2.486498759532142,0.4797826433300534,326
+rdflex,cutoff,Linear,Global linear,0.9,0.9294478527607362,10.96983032126306,2.626369168456619,326
+rdflex,cutoff,Linear,Global linear,0.95,0.9693251533742331,13.071359052196913,2.626369168456619,326
+rdflex,cutoff,Linear,LGBM,0.9,0.9233128834355828,10.942045228759646,2.6674077232846933,326
+rdflex,cutoff,Linear,LGBM,0.95,0.9693251533742331,13.038251072421996,2.6674077232846933,326
+rdflex,cutoff,Linear,Linear,0.9,0.9233128834355828,11.131059324216471,2.6748339112829975,326
+rdflex,cutoff,Linear,Linear,0.95,0.9693251533742331,13.263475258693452,2.6748339112829975,326
+rdflex,cutoff,Linear,Stacked,0.9,0.9325153374233128,10.691859937634922,2.5594401237673474,326
+rdflex,cutoff,Linear,Stacked,0.95,0.9723926380368099,12.740136910753437,2.5594401237673474,326
+rdflex,cutoff,Stacked,Global linear,0.9,0.9325153374233128,2.187332918383539,0.5141329649425767,326
+rdflex,cutoff,Stacked,Global linear,0.95,0.9723926380368099,2.606367929635302,0.5141329649425767,326
+rdflex,cutoff,Stacked,LGBM,0.9,0.9447852760736196,2.084406901521554,0.4842950492144703,326
+rdflex,cutoff,Stacked,LGBM,0.95,0.9785276073619632,2.4837240160272946,0.4842950492144703,326
+rdflex,cutoff,Stacked,Linear,0.9,0.9447852760736196,2.2538049373913993,0.508694038083471,326
+rdflex,cutoff,Stacked,Linear,0.95,0.9785276073619632,2.685574225624405,0.508694038083471,326
+rdflex,cutoff,Stacked,Stacked,0.9,0.9386503067484663,2.0705037128623642,0.4572681904124187,326
+rdflex,cutoff,Stacked,Stacked,0.95,0.9723926380368099,2.4671573449291615,0.4572681904124187,326
+rdflex,cutoff and score,Global linear,Global linear,0.9,0.9294478527607362,10.984587110958579,2.6446283025145436,326
+rdflex,cutoff and score,Global linear,Global linear,0.95,0.9662576687116564,13.088942851664987,2.6446283025145436,326
+rdflex,cutoff and score,Global linear,LGBM,0.9,0.9233128834355828,10.870122796118423,2.648249987515053,326
+rdflex,cutoff and score,Global linear,LGBM,0.95,0.9723926380368099,12.952550208012214,2.648249987515053,326
+rdflex,cutoff and score,Global linear,Linear,0.9,0.9294478527607362,11.098043415128812,2.6693484889896295,326
+rdflex,cutoff and score,Global linear,Linear,0.95,0.9662576687116564,13.2241343765211,2.6693484889896295,326
+rdflex,cutoff and score,Global linear,Stacked,0.9,0.9325153374233128,11.024150780216528,2.6631559704339027,326
+rdflex,cutoff and score,Global linear,Stacked,0.95,0.9754601226993865,13.136085871305921,2.6631559704339027,326
+rdflex,cutoff and score,LGBM,Global linear,0.9,0.9539877300613497,2.257956465543234,0.5264796507587247,326
+rdflex,cutoff and score,LGBM,Global linear,0.95,0.9846625766871165,2.6905210765326406,0.5264796507587247,326
+rdflex,cutoff and score,LGBM,LGBM,0.9,0.941717791411043,2.2359247513814267,0.5489387615418274,326
+rdflex,cutoff and score,LGBM,LGBM,0.95,0.9723926380368099,2.664268669894578,0.5489387615418274,326
+rdflex,cutoff and score,LGBM,Linear,0.9,0.9478527607361963,2.3160632863139248,0.5050075341473197,326
+rdflex,cutoff and score,LGBM,Linear,0.95,0.9754601226993865,2.759759624024404,0.5050075341473197,326
+rdflex,cutoff and score,LGBM,Stacked,0.9,0.9601226993865031,2.193878214343003,0.5114408990796515,326
+rdflex,cutoff and score,LGBM,Stacked,0.95,0.9846625766871165,2.6141671308155803,0.5114408990796515,326
+rdflex,cutoff and score,Linear,Global linear,0.9,0.9233128834355828,11.051316738099423,2.6624951246668958,326
+rdflex,cutoff and score,Linear,Global linear,0.95,0.9723926380368099,13.168456106677372,2.6624951246668958,326
+rdflex,cutoff and score,Linear,LGBM,0.9,0.9325153374233128,11.065562202201255,2.704055114865783,326
+rdflex,cutoff and score,Linear,LGBM,0.95,0.9785276073619632,13.185430624120844,2.704055114865783,326
+rdflex,cutoff and score,Linear,Linear,0.9,0.9171779141104295,11.151760330244164,2.6684582802977146,326
+rdflex,cutoff and score,Linear,Linear,0.95,0.9693251533742331,13.288142028789716,2.6684582802977146,326
+rdflex,cutoff and score,Linear,Stacked,0.9,0.9233128834355828,11.033555140076382,2.6884837296469457,326
+rdflex,cutoff and score,Linear,Stacked,0.95,0.9662576687116564,13.147291857249563,2.6884837296469457,326
+rdflex,cutoff and score,Stacked,Global linear,0.9,0.9386503067484663,2.251694287300681,0.5052099074156524,326
+rdflex,cutoff and score,Stacked,Global linear,0.95,0.9785276073619632,2.683059230919715,0.5052099074156524,326
+rdflex,cutoff and score,Stacked,LGBM,0.9,0.941717791411043,2.1946654016721294,0.519886298323518,326
+rdflex,cutoff and score,Stacked,LGBM,0.95,0.9723926380368099,2.6151051223723325,0.519886298323518,326
+rdflex,cutoff and score,Stacked,Linear,0.9,0.950920245398773,2.2877015453427094,0.5078411000316226,326
+rdflex,cutoff and score,Stacked,Linear,0.95,0.99079754601227,2.7259645252194957,0.5078411000316226,326
+rdflex,cutoff and score,Stacked,Stacked,0.9,0.9601226993865031,2.300600920177222,0.512009913334145,326
+rdflex,cutoff and score,Stacked,Stacked,0.95,0.9846625766871165,2.7413350783705295,0.512009913334145,326
+rdflex,interacted cutoff and score,Global linear,Global linear,0.9,0.9325153374233128,10.969386823588044,2.614545970486749,326
+rdflex,interacted cutoff and score,Global linear,Global linear,0.95,0.9662576687116564,13.070830592122402,2.614545970486749,326
+rdflex,interacted cutoff and score,Global linear,LGBM,0.9,0.9294478527607362,10.980599639871068,2.6472526376983985,326
+rdflex,interacted cutoff and score,Global linear,LGBM,0.95,0.9693251533742331,13.084191486806215,2.6472526376983985,326
+rdflex,interacted cutoff and score,Global linear,Linear,0.9,0.9355828220858896,11.095137976446441,2.6490979607665173,326
+rdflex,interacted cutoff and score,Global linear,Linear,0.95,0.9662576687116564,13.220672332796704,2.6490979607665173,326
+rdflex,interacted cutoff and score,Global linear,Stacked,0.9,0.9325153374233128,10.876654155957675,2.6415760401301185,326
+rdflex,interacted cutoff and score,Global linear,Stacked,0.95,0.9693251533742331,12.960332803281034,2.6415760401301185,326
+rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.9386503067484663,2.270439492899479,0.5365503248447656,326
+rdflex,interacted cutoff and score,LGBM,Global linear,0.95,0.9815950920245399,2.705395521063984,0.5365503248447656,326
+rdflex,interacted cutoff and score,LGBM,LGBM,0.9,0.9355828220858896,2.2553637843436474,0.5282989469506607,326
+rdflex,interacted cutoff and score,LGBM,LGBM,0.95,0.9785276073619632,2.687431706335001,0.5282989469506607,326
+rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.9447852760736196,2.2724639722051823,0.5262233509403855,326
+rdflex,interacted cutoff and score,LGBM,Linear,0.95,0.9877300613496932,2.7078078369452334,0.5262233509403855,326
+rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.9325153374233128,2.205972754065301,0.5451035967865461,326
+rdflex,interacted cutoff and score,LGBM,Stacked,0.95,0.9846625766871165,2.6285786637792925,0.5451035967865461,326
+rdflex,interacted cutoff and score,Linear,Global linear,0.9,0.9202453987730062,11.03486852734835,2.6715934145619955,326
+rdflex,interacted cutoff and score,Linear,Global linear,0.95,0.9693251533742331,13.148856854711118,2.6715934145619955,326
+rdflex,interacted cutoff and score,Linear,LGBM,0.9,0.9355828220858896,11.391856775666463,2.77003196088274,326
+rdflex,interacted cutoff and score,Linear,LGBM,0.95,0.9754601226993865,13.574234589327128,2.77003196088274,326
+rdflex,interacted cutoff and score,Linear,Linear,0.9,0.9325153374233128,11.17411790401542,2.6806337671939513,326
+rdflex,interacted cutoff and score,Linear,Linear,0.95,0.9693251533742331,13.314782721101395,2.6806337671939513,326
+rdflex,interacted cutoff and score,Linear,Stacked,0.9,0.9202453987730062,11.153281258970079,2.748415774362402,326
+rdflex,interacted cutoff and score,Linear,Stacked,0.95,0.9723926380368099,13.289954327146848,2.748415774362402,326
+rdflex,interacted cutoff and score,Stacked,Global linear,0.9,0.9294478527607362,2.3287051017657774,0.5642860899878326,326
+rdflex,interacted cutoff and score,Stacked,Global linear,0.95,0.9723926380368099,2.7748232762417477,0.5642860899878326,326
+rdflex,interacted cutoff and score,Stacked,LGBM,0.9,0.9355828220858896,2.2527721340224818,0.5169995794009677,326
+rdflex,interacted cutoff and score,Stacked,LGBM,0.95,0.9754601226993865,2.684343564504764,0.5169995794009677,326
+rdflex,interacted cutoff and score,Stacked,Linear,0.9,0.9386503067484663,2.3402504101672137,0.526173857770548,326
+rdflex,interacted cutoff and score,Stacked,Linear,0.95,0.9693251533742331,2.788580359721061,0.526173857770548,326
+rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.941717791411043,2.326640432634002,0.5287613366123899,326
+rdflex,interacted cutoff and score,Stacked,Stacked,0.95,0.9815950920245399,2.7723630712289946,0.5287613366123899,326
+rdrobust,cutoff,linear,linear,0.9,0.9263803680981595,10.898471694600076,2.6601440024294023,326
+rdrobust,cutoff,linear,linear,0.95,0.9693251533742331,12.986330004046948,2.6601440024294023,326
diff --git a/results/rdd/rdd_fuzzy_coverage_metadata.csv b/results/rdd/rdd_fuzzy_coverage_metadata.csv
index c088ee5..7c6910b 100644
--- a/results/rdd/rdd_fuzzy_coverage_metadata.csv
+++ b/results/rdd/rdd_fuzzy_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_fuzzy_coverage.py,2024-10-15 12:05:47,11919.275193691254,3.12.7
+0.9.dev0,rdd_fuzzy_coverage.py,2024-10-21 19:35:10,19841.012969970703,3.12.7

From 44aefe80e89311429095eb75eace0656b27f4d2d Mon Sep 17 00:00:00 2001
From: Sven Klaassen <47529404+SvenKlaassen@users.noreply.github.com>
Date: Mon, 2 Dec 2024 14:32:50 +0100
Subject: [PATCH 25/58] add RDD workflow trigger

---
 .github/workflows/sim.yml | 11 +++++++++++
 1 file changed, 11 insertions(+)

diff --git a/.github/workflows/sim.yml b/.github/workflows/sim.yml
index 92f8cda..fce7936 100644
--- a/.github/workflows/sim.yml
+++ b/.github/workflows/sim.yml
@@ -45,3 +45,14 @@ jobs:
 
           echo "HTTP Status: $RESPONSE"
           cat response.txt
+
+      - name: Trigger RDD Scripts Workflows
+        run: |
+          RESPONSE=$(curl -s -o response.txt -w "%{http_code}" -X POST \
+            -H "Authorization: token ${{ secrets.GITHUB_TOKEN }}" \
+            -H "Accept: application/vnd.github.everest-preview+json" \
+            https://api.github.com/repos/${{ github.repository }}/dispatches \
+            -d '{"event_type": "run-rdd-scripts", "client_payload": { "doubleml_py_branch": "${{ github.event.inputs.doubleml-py-branch }}", "target_branch": "${{ github.ref_name }}"}}')
+
+          echo "HTTP Status: $RESPONSE"
+          cat response.txt

From 9f9dba61fc7bf59db410442cc275bc90f2557772 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Mon, 2 Dec 2024 14:40:41 +0000
Subject: [PATCH 26/58] Update results from script:
 scripts/rdd/rdd_sharp_coverage.py

---
 results/rdd/rdd_sharp_coverage_metadata.csv | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/results/rdd/rdd_sharp_coverage_metadata.csv b/results/rdd/rdd_sharp_coverage_metadata.csv
index 8fe5f1b..eaab4d4 100644
--- a/results/rdd/rdd_sharp_coverage_metadata.csv
+++ b/results/rdd/rdd_sharp_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_sharp_coverage.py,2024-10-21 15:13:55,4153.726145505905,3.12.7
+0.9.dev0,rdd_sharp_coverage.py,2024-12-02 14:40:41,4122.115155220032,3.12.7

From a378a47002869cd2e4cb00d49b99e80bae506c7f Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Mon, 2 Dec 2024 19:02:59 +0000
Subject: [PATCH 27/58] Update results from script:
 scripts/rdd/rdd_fuzzy_coverage.py

---
 results/rdd/rdd_fuzzy_coverage.csv          | 196 ++++++++++----------
 results/rdd/rdd_fuzzy_coverage_metadata.csv |   2 +-
 2 files changed, 99 insertions(+), 99 deletions(-)

diff --git a/results/rdd/rdd_fuzzy_coverage.csv b/results/rdd/rdd_fuzzy_coverage.csv
index 5497bfd..a88a82a 100644
--- a/results/rdd/rdd_fuzzy_coverage.csv
+++ b/results/rdd/rdd_fuzzy_coverage.csv
@@ -1,99 +1,99 @@
 Method,fs specification,Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-rdflex,cutoff,Global linear,Global linear,0.9,0.9294478527607362,11.003281519552571,2.651668091366742,326
-rdflex,cutoff,Global linear,Global linear,0.95,0.9662576687116564,13.111218613444718,2.651668091366742,326
-rdflex,cutoff,Global linear,LGBM,0.9,0.9263803680981595,11.026796633476012,2.676212872142164,326
-rdflex,cutoff,Global linear,LGBM,0.95,0.9723926380368099,13.139238599920793,2.676212872142164,326
-rdflex,cutoff,Global linear,Linear,0.9,0.9263803680981595,11.061928208835385,2.6694105241913504,326
-rdflex,cutoff,Global linear,Linear,0.95,0.9662576687116564,13.181100453946152,2.6694105241913504,326
-rdflex,cutoff,Global linear,Stacked,0.9,0.9263803680981595,10.75270381540699,2.660157382556207,326
-rdflex,cutoff,Global linear,Stacked,0.95,0.9631901840490797,12.812636862821531,2.660157382556207,326
-rdflex,cutoff,LGBM,Global linear,0.9,0.9355828220858896,2.1367788053015517,0.48144779191064846,326
-rdflex,cutoff,LGBM,Global linear,0.95,0.9662576687116564,2.5461289884386313,0.48144779191064846,326
-rdflex,cutoff,LGBM,LGBM,0.9,0.941717791411043,2.118982251356838,0.49791701276459366,326
-rdflex,cutoff,LGBM,LGBM,0.95,0.9815950920245399,2.524923086461073,0.49791701276459366,326
-rdflex,cutoff,LGBM,Linear,0.9,0.9539877300613497,2.1750418199492105,0.4820841235532899,326
-rdflex,cutoff,LGBM,Linear,0.95,0.99079754601227,2.5917221825201815,0.4820841235532899,326
-rdflex,cutoff,LGBM,Stacked,0.9,0.9202453987730062,2.086735539677055,0.4797826433300534,326
-rdflex,cutoff,LGBM,Stacked,0.95,0.9723926380368099,2.486498759532142,0.4797826433300534,326
-rdflex,cutoff,Linear,Global linear,0.9,0.9294478527607362,10.96983032126306,2.626369168456619,326
-rdflex,cutoff,Linear,Global linear,0.95,0.9693251533742331,13.071359052196913,2.626369168456619,326
-rdflex,cutoff,Linear,LGBM,0.9,0.9233128834355828,10.942045228759646,2.6674077232846933,326
-rdflex,cutoff,Linear,LGBM,0.95,0.9693251533742331,13.038251072421996,2.6674077232846933,326
-rdflex,cutoff,Linear,Linear,0.9,0.9233128834355828,11.131059324216471,2.6748339112829975,326
-rdflex,cutoff,Linear,Linear,0.95,0.9693251533742331,13.263475258693452,2.6748339112829975,326
-rdflex,cutoff,Linear,Stacked,0.9,0.9325153374233128,10.691859937634922,2.5594401237673474,326
-rdflex,cutoff,Linear,Stacked,0.95,0.9723926380368099,12.740136910753437,2.5594401237673474,326
-rdflex,cutoff,Stacked,Global linear,0.9,0.9325153374233128,2.187332918383539,0.5141329649425767,326
-rdflex,cutoff,Stacked,Global linear,0.95,0.9723926380368099,2.606367929635302,0.5141329649425767,326
-rdflex,cutoff,Stacked,LGBM,0.9,0.9447852760736196,2.084406901521554,0.4842950492144703,326
-rdflex,cutoff,Stacked,LGBM,0.95,0.9785276073619632,2.4837240160272946,0.4842950492144703,326
-rdflex,cutoff,Stacked,Linear,0.9,0.9447852760736196,2.2538049373913993,0.508694038083471,326
-rdflex,cutoff,Stacked,Linear,0.95,0.9785276073619632,2.685574225624405,0.508694038083471,326
-rdflex,cutoff,Stacked,Stacked,0.9,0.9386503067484663,2.0705037128623642,0.4572681904124187,326
-rdflex,cutoff,Stacked,Stacked,0.95,0.9723926380368099,2.4671573449291615,0.4572681904124187,326
-rdflex,cutoff and score,Global linear,Global linear,0.9,0.9294478527607362,10.984587110958579,2.6446283025145436,326
-rdflex,cutoff and score,Global linear,Global linear,0.95,0.9662576687116564,13.088942851664987,2.6446283025145436,326
-rdflex,cutoff and score,Global linear,LGBM,0.9,0.9233128834355828,10.870122796118423,2.648249987515053,326
-rdflex,cutoff and score,Global linear,LGBM,0.95,0.9723926380368099,12.952550208012214,2.648249987515053,326
-rdflex,cutoff and score,Global linear,Linear,0.9,0.9294478527607362,11.098043415128812,2.6693484889896295,326
-rdflex,cutoff and score,Global linear,Linear,0.95,0.9662576687116564,13.2241343765211,2.6693484889896295,326
-rdflex,cutoff and score,Global linear,Stacked,0.9,0.9325153374233128,11.024150780216528,2.6631559704339027,326
-rdflex,cutoff and score,Global linear,Stacked,0.95,0.9754601226993865,13.136085871305921,2.6631559704339027,326
-rdflex,cutoff and score,LGBM,Global linear,0.9,0.9539877300613497,2.257956465543234,0.5264796507587247,326
-rdflex,cutoff and score,LGBM,Global linear,0.95,0.9846625766871165,2.6905210765326406,0.5264796507587247,326
-rdflex,cutoff and score,LGBM,LGBM,0.9,0.941717791411043,2.2359247513814267,0.5489387615418274,326
-rdflex,cutoff and score,LGBM,LGBM,0.95,0.9723926380368099,2.664268669894578,0.5489387615418274,326
-rdflex,cutoff and score,LGBM,Linear,0.9,0.9478527607361963,2.3160632863139248,0.5050075341473197,326
-rdflex,cutoff and score,LGBM,Linear,0.95,0.9754601226993865,2.759759624024404,0.5050075341473197,326
-rdflex,cutoff and score,LGBM,Stacked,0.9,0.9601226993865031,2.193878214343003,0.5114408990796515,326
-rdflex,cutoff and score,LGBM,Stacked,0.95,0.9846625766871165,2.6141671308155803,0.5114408990796515,326
-rdflex,cutoff and score,Linear,Global linear,0.9,0.9233128834355828,11.051316738099423,2.6624951246668958,326
-rdflex,cutoff and score,Linear,Global linear,0.95,0.9723926380368099,13.168456106677372,2.6624951246668958,326
-rdflex,cutoff and score,Linear,LGBM,0.9,0.9325153374233128,11.065562202201255,2.704055114865783,326
-rdflex,cutoff and score,Linear,LGBM,0.95,0.9785276073619632,13.185430624120844,2.704055114865783,326
-rdflex,cutoff and score,Linear,Linear,0.9,0.9171779141104295,11.151760330244164,2.6684582802977146,326
-rdflex,cutoff and score,Linear,Linear,0.95,0.9693251533742331,13.288142028789716,2.6684582802977146,326
-rdflex,cutoff and score,Linear,Stacked,0.9,0.9233128834355828,11.033555140076382,2.6884837296469457,326
-rdflex,cutoff and score,Linear,Stacked,0.95,0.9662576687116564,13.147291857249563,2.6884837296469457,326
-rdflex,cutoff and score,Stacked,Global linear,0.9,0.9386503067484663,2.251694287300681,0.5052099074156524,326
-rdflex,cutoff and score,Stacked,Global linear,0.95,0.9785276073619632,2.683059230919715,0.5052099074156524,326
-rdflex,cutoff and score,Stacked,LGBM,0.9,0.941717791411043,2.1946654016721294,0.519886298323518,326
-rdflex,cutoff and score,Stacked,LGBM,0.95,0.9723926380368099,2.6151051223723325,0.519886298323518,326
-rdflex,cutoff and score,Stacked,Linear,0.9,0.950920245398773,2.2877015453427094,0.5078411000316226,326
-rdflex,cutoff and score,Stacked,Linear,0.95,0.99079754601227,2.7259645252194957,0.5078411000316226,326
-rdflex,cutoff and score,Stacked,Stacked,0.9,0.9601226993865031,2.300600920177222,0.512009913334145,326
-rdflex,cutoff and score,Stacked,Stacked,0.95,0.9846625766871165,2.7413350783705295,0.512009913334145,326
-rdflex,interacted cutoff and score,Global linear,Global linear,0.9,0.9325153374233128,10.969386823588044,2.614545970486749,326
-rdflex,interacted cutoff and score,Global linear,Global linear,0.95,0.9662576687116564,13.070830592122402,2.614545970486749,326
-rdflex,interacted cutoff and score,Global linear,LGBM,0.9,0.9294478527607362,10.980599639871068,2.6472526376983985,326
-rdflex,interacted cutoff and score,Global linear,LGBM,0.95,0.9693251533742331,13.084191486806215,2.6472526376983985,326
-rdflex,interacted cutoff and score,Global linear,Linear,0.9,0.9355828220858896,11.095137976446441,2.6490979607665173,326
-rdflex,interacted cutoff and score,Global linear,Linear,0.95,0.9662576687116564,13.220672332796704,2.6490979607665173,326
-rdflex,interacted cutoff and score,Global linear,Stacked,0.9,0.9325153374233128,10.876654155957675,2.6415760401301185,326
-rdflex,interacted cutoff and score,Global linear,Stacked,0.95,0.9693251533742331,12.960332803281034,2.6415760401301185,326
-rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.9386503067484663,2.270439492899479,0.5365503248447656,326
-rdflex,interacted cutoff and score,LGBM,Global linear,0.95,0.9815950920245399,2.705395521063984,0.5365503248447656,326
-rdflex,interacted cutoff and score,LGBM,LGBM,0.9,0.9355828220858896,2.2553637843436474,0.5282989469506607,326
-rdflex,interacted cutoff and score,LGBM,LGBM,0.95,0.9785276073619632,2.687431706335001,0.5282989469506607,326
-rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.9447852760736196,2.2724639722051823,0.5262233509403855,326
-rdflex,interacted cutoff and score,LGBM,Linear,0.95,0.9877300613496932,2.7078078369452334,0.5262233509403855,326
-rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.9325153374233128,2.205972754065301,0.5451035967865461,326
-rdflex,interacted cutoff and score,LGBM,Stacked,0.95,0.9846625766871165,2.6285786637792925,0.5451035967865461,326
-rdflex,interacted cutoff and score,Linear,Global linear,0.9,0.9202453987730062,11.03486852734835,2.6715934145619955,326
-rdflex,interacted cutoff and score,Linear,Global linear,0.95,0.9693251533742331,13.148856854711118,2.6715934145619955,326
-rdflex,interacted cutoff and score,Linear,LGBM,0.9,0.9355828220858896,11.391856775666463,2.77003196088274,326
-rdflex,interacted cutoff and score,Linear,LGBM,0.95,0.9754601226993865,13.574234589327128,2.77003196088274,326
-rdflex,interacted cutoff and score,Linear,Linear,0.9,0.9325153374233128,11.17411790401542,2.6806337671939513,326
-rdflex,interacted cutoff and score,Linear,Linear,0.95,0.9693251533742331,13.314782721101395,2.6806337671939513,326
-rdflex,interacted cutoff and score,Linear,Stacked,0.9,0.9202453987730062,11.153281258970079,2.748415774362402,326
-rdflex,interacted cutoff and score,Linear,Stacked,0.95,0.9723926380368099,13.289954327146848,2.748415774362402,326
-rdflex,interacted cutoff and score,Stacked,Global linear,0.9,0.9294478527607362,2.3287051017657774,0.5642860899878326,326
-rdflex,interacted cutoff and score,Stacked,Global linear,0.95,0.9723926380368099,2.7748232762417477,0.5642860899878326,326
-rdflex,interacted cutoff and score,Stacked,LGBM,0.9,0.9355828220858896,2.2527721340224818,0.5169995794009677,326
-rdflex,interacted cutoff and score,Stacked,LGBM,0.95,0.9754601226993865,2.684343564504764,0.5169995794009677,326
-rdflex,interacted cutoff and score,Stacked,Linear,0.9,0.9386503067484663,2.3402504101672137,0.526173857770548,326
-rdflex,interacted cutoff and score,Stacked,Linear,0.95,0.9693251533742331,2.788580359721061,0.526173857770548,326
-rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.941717791411043,2.326640432634002,0.5287613366123899,326
-rdflex,interacted cutoff and score,Stacked,Stacked,0.95,0.9815950920245399,2.7723630712289946,0.5287613366123899,326
-rdrobust,cutoff,linear,linear,0.9,0.9263803680981595,10.898471694600076,2.6601440024294023,326
-rdrobust,cutoff,linear,linear,0.95,0.9693251533742331,12.986330004046948,2.6601440024294023,326
+rdflex,cutoff,Global linear,Global linear,0.9,0.9298780487804879,11.014787524857034,2.6402139662744033,328
+rdflex,cutoff,Global linear,Global linear,0.95,0.9664634146341463,13.124928864395418,2.6402139662744033,328
+rdflex,cutoff,Global linear,LGBM,0.9,0.926829268292683,11.056186854293065,2.663009525372308,328
+rdflex,cutoff,Global linear,LGBM,0.95,0.9725609756097561,13.174259208049836,2.663009525372308,328
+rdflex,cutoff,Global linear,Linear,0.9,0.926829268292683,11.0729582356916,2.657222292041521,328
+rdflex,cutoff,Global linear,Linear,0.95,0.9664634146341463,13.19424354159387,2.657222292041521,328
+rdflex,cutoff,Global linear,Stacked,0.9,0.926829268292683,10.764595024884207,2.6465839359208645,328
+rdflex,cutoff,Global linear,Stacked,0.95,0.9634146341463414,12.826806112854534,2.6465839359208645,328
+rdflex,cutoff,LGBM,Global linear,0.9,0.9359756097560976,2.1408620403476704,0.48178393250386253,328
+rdflex,cutoff,LGBM,Global linear,0.95,0.9664634146341463,2.550994463092225,0.48178393250386253,328
+rdflex,cutoff,LGBM,LGBM,0.9,0.9420731707317073,2.126100388937439,0.500366167259078,328
+rdflex,cutoff,LGBM,LGBM,0.95,0.9817073170731707,2.533404870533761,0.500366167259078,328
+rdflex,cutoff,LGBM,Linear,0.9,0.9542682926829268,2.176688652083384,0.479588173670183,328
+rdflex,cutoff,LGBM,Linear,0.95,0.9908536585365854,2.5936845040414864,0.479588173670183,328
+rdflex,cutoff,LGBM,Stacked,0.9,0.9207317073170732,2.0908177039389026,0.4804235027827051,328
+rdflex,cutoff,LGBM,Stacked,0.95,0.9725609756097561,2.49136295826758,0.4804235027827051,328
+rdflex,cutoff,Linear,Global linear,0.9,0.9298780487804879,10.98193611629228,2.6143332366644914,328
+rdflex,cutoff,Linear,Global linear,0.95,0.9695121951219512,13.085783996686027,2.6143332366644914,328
+rdflex,cutoff,Linear,LGBM,0.9,0.9237804878048781,10.958897850408714,2.655591842484404,328
+rdflex,cutoff,Linear,LGBM,0.95,0.9695121951219512,13.05833220969527,2.655591842484404,328
+rdflex,cutoff,Linear,Linear,0.9,0.9237804878048781,11.145684920911066,2.6610924563161404,328
+rdflex,cutoff,Linear,Linear,0.95,0.9695121951219512,13.280902732058932,2.6610924563161404,328
+rdflex,cutoff,Linear,Stacked,0.9,0.9329268292682927,10.71779859931537,2.54726739380102,328
+rdflex,cutoff,Linear,Stacked,0.95,0.9725609756097561,12.771044732499906,2.54726739380102,328
+rdflex,cutoff,Stacked,Global linear,0.9,0.9329268292682927,2.1897603091327085,0.5119088893737982,328
+rdflex,cutoff,Stacked,Global linear,0.95,0.9725609756097561,2.6092603441132973,0.5119088893737982,328
+rdflex,cutoff,Stacked,LGBM,0.9,0.9451219512195121,2.0888656986777563,0.4841501391478207,328
+rdflex,cutoff,Stacked,LGBM,0.95,0.9786585365853658,2.489037000536879,0.4841501391478207,328
+rdflex,cutoff,Stacked,Linear,0.9,0.9451219512195121,2.2564564079702487,0.5075882022019412,328
+rdflex,cutoff,Stacked,Linear,0.95,0.9786585365853658,2.6887336476881445,0.5075882022019412,328
+rdflex,cutoff,Stacked,Stacked,0.9,0.9390243902439024,2.0746872031402495,0.45607506021396776,328
+rdflex,cutoff,Stacked,Stacked,0.95,0.9725609756097561,2.472142281059633,0.45607506021396776,328
+rdflex,cutoff and score,Global linear,Global linear,0.9,0.9298780487804879,10.995842039549206,2.63271762436908,328
+rdflex,cutoff and score,Global linear,Global linear,0.95,0.9664634146341463,13.102353926258344,2.63271762436908,328
+rdflex,cutoff and score,Global linear,LGBM,0.9,0.9237804878048781,10.89284687767913,2.6357930550672526,328
+rdflex,cutoff and score,Global linear,LGBM,0.95,0.9725609756097561,12.979627621291403,2.6357930550672526,328
+rdflex,cutoff and score,Global linear,Linear,0.9,0.9298780487804879,11.108789922981721,2.656038691769452,328
+rdflex,cutoff and score,Global linear,Linear,0.95,0.9664634146341463,13.236939630439233,2.656038691769452,328
+rdflex,cutoff and score,Global linear,Stacked,0.9,0.9329268292682927,11.040949217450864,2.6504947759869,328
+rdflex,cutoff and score,Global linear,Stacked,0.95,0.975609756097561,13.156102443866772,2.6504947759869,328
+rdflex,cutoff and score,LGBM,Global linear,0.9,0.9542682926829268,2.2612147518852206,0.5272251367500654,328
+rdflex,cutoff and score,LGBM,Global linear,0.95,0.9847560975609756,2.6944035641759023,0.5272251367500654,328
+rdflex,cutoff and score,LGBM,LGBM,0.9,0.9420731707317073,2.2387554646202474,0.5478247921924015,328
+rdflex,cutoff and score,LGBM,LGBM,0.95,0.9725609756097561,2.667641672761059,0.5478247921924015,328
+rdflex,cutoff and score,LGBM,Linear,0.9,0.948170731707317,2.3171811850550545,0.5051261837806915,328
+rdflex,cutoff and score,LGBM,Linear,0.95,0.975609756097561,2.7610916825340954,0.5051261837806915,328
+rdflex,cutoff and score,LGBM,Stacked,0.9,0.9603658536585366,2.201625577273113,0.5098335087352732,328
+rdflex,cutoff and score,LGBM,Stacked,0.95,0.9847560975609756,2.623398683136937,0.5098335087352732,328
+rdflex,cutoff and score,Linear,Global linear,0.9,0.9237804878048781,11.061867460080087,2.6486203182946912,328
+rdflex,cutoff and score,Linear,Global linear,0.95,0.9725609756097561,13.181028067339504,2.6486203182946912,328
+rdflex,cutoff and score,Linear,LGBM,0.9,0.9329268292682927,11.085721033397748,2.689203787826424,328
+rdflex,cutoff and score,Linear,LGBM,0.95,0.9786585365853658,13.20945135305876,2.689203787826424,328
+rdflex,cutoff and score,Linear,Linear,0.9,0.9176829268292683,11.162947737923707,2.6572897264431106,328
+rdflex,cutoff and score,Linear,Linear,0.95,0.9695121951219512,13.301472647255087,2.6572897264431106,328
+rdflex,cutoff and score,Linear,Stacked,0.9,0.9237804878048781,11.053700823955918,2.674524865733552,328
+rdflex,cutoff and score,Linear,Stacked,0.95,0.9664634146341463,13.171296920193067,2.674524865733552,328
+rdflex,cutoff and score,Stacked,Global linear,0.9,0.9390243902439024,2.2530848703437836,0.5036704456090698,328
+rdflex,cutoff and score,Stacked,Global linear,0.95,0.9786585365853658,2.684716212816058,0.5036704456090698,328
+rdflex,cutoff and score,Stacked,LGBM,0.9,0.9420731707317073,2.195011783732391,0.5184948484663574,328
+rdflex,cutoff and score,Stacked,LGBM,0.95,0.9725609756097561,2.6155178620543804,0.5184948484663574,328
+rdflex,cutoff and score,Stacked,Linear,0.9,0.9512195121951219,2.2899957244331177,0.5052413300366605,328
+rdflex,cutoff and score,Stacked,Linear,0.95,0.9908536585365854,2.7286982082157265,0.5052413300366605,328
+rdflex,cutoff and score,Stacked,Stacked,0.9,0.9603658536585366,2.301765158448579,0.5108905191856478,328
+rdflex,cutoff and score,Stacked,Stacked,0.95,0.9847560975609756,2.742722353836196,0.5108905191856478,328
+rdflex,interacted cutoff and score,Global linear,Global linear,0.9,0.9329268292682927,10.98152612533236,2.603169598522485,328
+rdflex,interacted cutoff and score,Global linear,Global linear,0.95,0.9664634146341463,13.08529546232512,2.603169598522485,328
+rdflex,interacted cutoff and score,Global linear,LGBM,0.9,0.9298780487804879,10.99049049620265,2.632969346147504,328
+rdflex,interacted cutoff and score,Global linear,LGBM,0.95,0.9695121951219512,13.095977169050833,2.632969346147504,328
+rdflex,interacted cutoff and score,Global linear,Linear,0.9,0.9359756097560976,11.10786403716801,2.635951731402889,328
+rdflex,interacted cutoff and score,Global linear,Linear,0.95,0.9664634146341463,13.235836369444494,2.635951731402889,328
+rdflex,interacted cutoff and score,Global linear,Stacked,0.9,0.9329268292682927,10.913822712702768,2.630135237508495,328
+rdflex,interacted cutoff and score,Global linear,Stacked,0.95,0.9695121951219512,13.004621870334814,2.630135237508495,328
+rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.9390243902439024,2.2794687231649515,0.5419687621013095,328
+rdflex,interacted cutoff and score,LGBM,Global linear,0.95,0.9817073170731707,2.716154512525884,0.5419687621013095,328
+rdflex,interacted cutoff and score,LGBM,LGBM,0.9,0.9359756097560976,2.2587577941053927,0.5278444852222671,328
+rdflex,interacted cutoff and score,LGBM,LGBM,0.95,0.9786585365853658,2.691475918407857,0.5278444852222671,328
+rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.9451219512195121,2.274420475664184,0.5250335049560754,328
+rdflex,interacted cutoff and score,LGBM,Linear,0.95,0.9878048780487805,2.710139154609273,0.5250335049560754,328
+rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.9329268292682927,2.210344093618034,0.5447338309672924,328
+rdflex,interacted cutoff and score,LGBM,Stacked,0.95,0.9847560975609756,2.6337874361266724,0.5447338309672924,328
+rdflex,interacted cutoff and score,Linear,Global linear,0.9,0.9207317073170732,11.04676677004346,2.65801770920311,328
+rdflex,interacted cutoff and score,Linear,Global linear,0.95,0.9695121951219512,13.163034485340146,2.65801770920311,328
+rdflex,interacted cutoff and score,Linear,LGBM,0.9,0.9359756097560976,11.420715187719008,2.7600510207095925,328
+rdflex,interacted cutoff and score,Linear,LGBM,0.95,0.975609756097561,13.608621508228133,2.7600510207095925,328
+rdflex,interacted cutoff and score,Linear,Linear,0.9,0.9329268292682927,11.182065032541443,2.6678840377562207,328
+rdflex,interacted cutoff and score,Linear,Linear,0.95,0.9695121951219512,13.324252308811996,2.6678840377562207,328
+rdflex,interacted cutoff and score,Linear,Stacked,0.9,0.9207317073170732,11.179341833779677,2.737095486322336,328
+rdflex,interacted cutoff and score,Linear,Stacked,0.95,0.9725609756097561,13.321007417346669,2.737095486322336,328
+rdflex,interacted cutoff and score,Stacked,Global linear,0.9,0.9298780487804879,2.33175306213734,0.564578641351739,328
+rdflex,interacted cutoff and score,Stacked,Global linear,0.95,0.9725609756097561,2.778455145033404,0.564578641351739,328
+rdflex,interacted cutoff and score,Stacked,LGBM,0.9,0.9359756097560976,2.2561521994383473,0.5155050289769663,328
+rdflex,interacted cutoff and score,Stacked,LGBM,0.95,0.975609756097561,2.6883711608646683,0.5155050289769663,328
+rdflex,interacted cutoff and score,Stacked,Linear,0.9,0.9390243902439024,2.3456922453937534,0.5278125836408509,328
+rdflex,interacted cutoff and score,Stacked,Linear,0.95,0.9695121951219512,2.7950647063395415,0.5278125836408509,328
+rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.9420731707317073,2.330264554451441,0.5266693508368335,328
+rdflex,interacted cutoff and score,Stacked,Stacked,0.95,0.9817073170731707,2.7766814787282263,0.5266693508368335,328
+rdrobust,cutoff,linear,linear,0.9,0.926829268292683,10.913917661821893,2.6462280044256774,328
+rdrobust,cutoff,linear,linear,0.95,0.9695121951219512,13.004735009188504,2.6462280044256774,328
diff --git a/results/rdd/rdd_fuzzy_coverage_metadata.csv b/results/rdd/rdd_fuzzy_coverage_metadata.csv
index 7c6910b..ea8eaa3 100644
--- a/results/rdd/rdd_fuzzy_coverage_metadata.csv
+++ b/results/rdd/rdd_fuzzy_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_fuzzy_coverage.py,2024-10-21 19:35:10,19841.012969970703,3.12.7
+0.9.dev0,rdd_fuzzy_coverage.py,2024-12-02 19:02:59,19854.447350025177,3.12.7

From 567faa5d30b6c9eab6c1d7919878e0b5c87f3393 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Mon, 6 Jan 2025 13:53:35 +0000
Subject: [PATCH 28/58] Update results from script:
 scripts/rdd/rdd_sharp_coverage.py

---
 results/rdd/rdd_sharp_coverage_metadata.csv | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/results/rdd/rdd_sharp_coverage_metadata.csv b/results/rdd/rdd_sharp_coverage_metadata.csv
index eaab4d4..3fa91a4 100644
--- a/results/rdd/rdd_sharp_coverage_metadata.csv
+++ b/results/rdd/rdd_sharp_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_sharp_coverage.py,2024-12-02 14:40:41,4122.115155220032,3.12.7
+0.9.dev0,rdd_sharp_coverage.py,2025-01-06 13:53:34,4068.1591482162476,3.12.8

From e67f102c96feda746c0eb3cfeafe3260ed979e3a Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Mon, 6 Jan 2025 18:16:59 +0000
Subject: [PATCH 29/58] Update results from script:
 scripts/rdd/rdd_fuzzy_coverage.py

---
 results/rdd/rdd_fuzzy_coverage.csv          | 196 ++++++++++----------
 results/rdd/rdd_fuzzy_coverage_metadata.csv |   2 +-
 2 files changed, 99 insertions(+), 99 deletions(-)

diff --git a/results/rdd/rdd_fuzzy_coverage.csv b/results/rdd/rdd_fuzzy_coverage.csv
index a88a82a..aae1460 100644
--- a/results/rdd/rdd_fuzzy_coverage.csv
+++ b/results/rdd/rdd_fuzzy_coverage.csv
@@ -1,99 +1,99 @@
 Method,fs specification,Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-rdflex,cutoff,Global linear,Global linear,0.9,0.9298780487804879,11.014787524857034,2.6402139662744033,328
-rdflex,cutoff,Global linear,Global linear,0.95,0.9664634146341463,13.124928864395418,2.6402139662744033,328
-rdflex,cutoff,Global linear,LGBM,0.9,0.926829268292683,11.056186854293065,2.663009525372308,328
-rdflex,cutoff,Global linear,LGBM,0.95,0.9725609756097561,13.174259208049836,2.663009525372308,328
-rdflex,cutoff,Global linear,Linear,0.9,0.926829268292683,11.0729582356916,2.657222292041521,328
-rdflex,cutoff,Global linear,Linear,0.95,0.9664634146341463,13.19424354159387,2.657222292041521,328
-rdflex,cutoff,Global linear,Stacked,0.9,0.926829268292683,10.764595024884207,2.6465839359208645,328
-rdflex,cutoff,Global linear,Stacked,0.95,0.9634146341463414,12.826806112854534,2.6465839359208645,328
-rdflex,cutoff,LGBM,Global linear,0.9,0.9359756097560976,2.1408620403476704,0.48178393250386253,328
-rdflex,cutoff,LGBM,Global linear,0.95,0.9664634146341463,2.550994463092225,0.48178393250386253,328
-rdflex,cutoff,LGBM,LGBM,0.9,0.9420731707317073,2.126100388937439,0.500366167259078,328
-rdflex,cutoff,LGBM,LGBM,0.95,0.9817073170731707,2.533404870533761,0.500366167259078,328
-rdflex,cutoff,LGBM,Linear,0.9,0.9542682926829268,2.176688652083384,0.479588173670183,328
-rdflex,cutoff,LGBM,Linear,0.95,0.9908536585365854,2.5936845040414864,0.479588173670183,328
-rdflex,cutoff,LGBM,Stacked,0.9,0.9207317073170732,2.0908177039389026,0.4804235027827051,328
-rdflex,cutoff,LGBM,Stacked,0.95,0.9725609756097561,2.49136295826758,0.4804235027827051,328
-rdflex,cutoff,Linear,Global linear,0.9,0.9298780487804879,10.98193611629228,2.6143332366644914,328
-rdflex,cutoff,Linear,Global linear,0.95,0.9695121951219512,13.085783996686027,2.6143332366644914,328
-rdflex,cutoff,Linear,LGBM,0.9,0.9237804878048781,10.958897850408714,2.655591842484404,328
-rdflex,cutoff,Linear,LGBM,0.95,0.9695121951219512,13.05833220969527,2.655591842484404,328
-rdflex,cutoff,Linear,Linear,0.9,0.9237804878048781,11.145684920911066,2.6610924563161404,328
-rdflex,cutoff,Linear,Linear,0.95,0.9695121951219512,13.280902732058932,2.6610924563161404,328
-rdflex,cutoff,Linear,Stacked,0.9,0.9329268292682927,10.71779859931537,2.54726739380102,328
-rdflex,cutoff,Linear,Stacked,0.95,0.9725609756097561,12.771044732499906,2.54726739380102,328
-rdflex,cutoff,Stacked,Global linear,0.9,0.9329268292682927,2.1897603091327085,0.5119088893737982,328
-rdflex,cutoff,Stacked,Global linear,0.95,0.9725609756097561,2.6092603441132973,0.5119088893737982,328
-rdflex,cutoff,Stacked,LGBM,0.9,0.9451219512195121,2.0888656986777563,0.4841501391478207,328
-rdflex,cutoff,Stacked,LGBM,0.95,0.9786585365853658,2.489037000536879,0.4841501391478207,328
-rdflex,cutoff,Stacked,Linear,0.9,0.9451219512195121,2.2564564079702487,0.5075882022019412,328
-rdflex,cutoff,Stacked,Linear,0.95,0.9786585365853658,2.6887336476881445,0.5075882022019412,328
-rdflex,cutoff,Stacked,Stacked,0.9,0.9390243902439024,2.0746872031402495,0.45607506021396776,328
-rdflex,cutoff,Stacked,Stacked,0.95,0.9725609756097561,2.472142281059633,0.45607506021396776,328
-rdflex,cutoff and score,Global linear,Global linear,0.9,0.9298780487804879,10.995842039549206,2.63271762436908,328
-rdflex,cutoff and score,Global linear,Global linear,0.95,0.9664634146341463,13.102353926258344,2.63271762436908,328
-rdflex,cutoff and score,Global linear,LGBM,0.9,0.9237804878048781,10.89284687767913,2.6357930550672526,328
-rdflex,cutoff and score,Global linear,LGBM,0.95,0.9725609756097561,12.979627621291403,2.6357930550672526,328
-rdflex,cutoff and score,Global linear,Linear,0.9,0.9298780487804879,11.108789922981721,2.656038691769452,328
-rdflex,cutoff and score,Global linear,Linear,0.95,0.9664634146341463,13.236939630439233,2.656038691769452,328
-rdflex,cutoff and score,Global linear,Stacked,0.9,0.9329268292682927,11.040949217450864,2.6504947759869,328
-rdflex,cutoff and score,Global linear,Stacked,0.95,0.975609756097561,13.156102443866772,2.6504947759869,328
-rdflex,cutoff and score,LGBM,Global linear,0.9,0.9542682926829268,2.2612147518852206,0.5272251367500654,328
-rdflex,cutoff and score,LGBM,Global linear,0.95,0.9847560975609756,2.6944035641759023,0.5272251367500654,328
-rdflex,cutoff and score,LGBM,LGBM,0.9,0.9420731707317073,2.2387554646202474,0.5478247921924015,328
-rdflex,cutoff and score,LGBM,LGBM,0.95,0.9725609756097561,2.667641672761059,0.5478247921924015,328
-rdflex,cutoff and score,LGBM,Linear,0.9,0.948170731707317,2.3171811850550545,0.5051261837806915,328
-rdflex,cutoff and score,LGBM,Linear,0.95,0.975609756097561,2.7610916825340954,0.5051261837806915,328
-rdflex,cutoff and score,LGBM,Stacked,0.9,0.9603658536585366,2.201625577273113,0.5098335087352732,328
-rdflex,cutoff and score,LGBM,Stacked,0.95,0.9847560975609756,2.623398683136937,0.5098335087352732,328
-rdflex,cutoff and score,Linear,Global linear,0.9,0.9237804878048781,11.061867460080087,2.6486203182946912,328
-rdflex,cutoff and score,Linear,Global linear,0.95,0.9725609756097561,13.181028067339504,2.6486203182946912,328
-rdflex,cutoff and score,Linear,LGBM,0.9,0.9329268292682927,11.085721033397748,2.689203787826424,328
-rdflex,cutoff and score,Linear,LGBM,0.95,0.9786585365853658,13.20945135305876,2.689203787826424,328
-rdflex,cutoff and score,Linear,Linear,0.9,0.9176829268292683,11.162947737923707,2.6572897264431106,328
-rdflex,cutoff and score,Linear,Linear,0.95,0.9695121951219512,13.301472647255087,2.6572897264431106,328
-rdflex,cutoff and score,Linear,Stacked,0.9,0.9237804878048781,11.053700823955918,2.674524865733552,328
-rdflex,cutoff and score,Linear,Stacked,0.95,0.9664634146341463,13.171296920193067,2.674524865733552,328
-rdflex,cutoff and score,Stacked,Global linear,0.9,0.9390243902439024,2.2530848703437836,0.5036704456090698,328
-rdflex,cutoff and score,Stacked,Global linear,0.95,0.9786585365853658,2.684716212816058,0.5036704456090698,328
-rdflex,cutoff and score,Stacked,LGBM,0.9,0.9420731707317073,2.195011783732391,0.5184948484663574,328
-rdflex,cutoff and score,Stacked,LGBM,0.95,0.9725609756097561,2.6155178620543804,0.5184948484663574,328
-rdflex,cutoff and score,Stacked,Linear,0.9,0.9512195121951219,2.2899957244331177,0.5052413300366605,328
-rdflex,cutoff and score,Stacked,Linear,0.95,0.9908536585365854,2.7286982082157265,0.5052413300366605,328
-rdflex,cutoff and score,Stacked,Stacked,0.9,0.9603658536585366,2.301765158448579,0.5108905191856478,328
-rdflex,cutoff and score,Stacked,Stacked,0.95,0.9847560975609756,2.742722353836196,0.5108905191856478,328
-rdflex,interacted cutoff and score,Global linear,Global linear,0.9,0.9329268292682927,10.98152612533236,2.603169598522485,328
-rdflex,interacted cutoff and score,Global linear,Global linear,0.95,0.9664634146341463,13.08529546232512,2.603169598522485,328
-rdflex,interacted cutoff and score,Global linear,LGBM,0.9,0.9298780487804879,10.99049049620265,2.632969346147504,328
-rdflex,interacted cutoff and score,Global linear,LGBM,0.95,0.9695121951219512,13.095977169050833,2.632969346147504,328
-rdflex,interacted cutoff and score,Global linear,Linear,0.9,0.9359756097560976,11.10786403716801,2.635951731402889,328
-rdflex,interacted cutoff and score,Global linear,Linear,0.95,0.9664634146341463,13.235836369444494,2.635951731402889,328
-rdflex,interacted cutoff and score,Global linear,Stacked,0.9,0.9329268292682927,10.913822712702768,2.630135237508495,328
-rdflex,interacted cutoff and score,Global linear,Stacked,0.95,0.9695121951219512,13.004621870334814,2.630135237508495,328
-rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.9390243902439024,2.2794687231649515,0.5419687621013095,328
-rdflex,interacted cutoff and score,LGBM,Global linear,0.95,0.9817073170731707,2.716154512525884,0.5419687621013095,328
-rdflex,interacted cutoff and score,LGBM,LGBM,0.9,0.9359756097560976,2.2587577941053927,0.5278444852222671,328
-rdflex,interacted cutoff and score,LGBM,LGBM,0.95,0.9786585365853658,2.691475918407857,0.5278444852222671,328
-rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.9451219512195121,2.274420475664184,0.5250335049560754,328
-rdflex,interacted cutoff and score,LGBM,Linear,0.95,0.9878048780487805,2.710139154609273,0.5250335049560754,328
-rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.9329268292682927,2.210344093618034,0.5447338309672924,328
-rdflex,interacted cutoff and score,LGBM,Stacked,0.95,0.9847560975609756,2.6337874361266724,0.5447338309672924,328
-rdflex,interacted cutoff and score,Linear,Global linear,0.9,0.9207317073170732,11.04676677004346,2.65801770920311,328
-rdflex,interacted cutoff and score,Linear,Global linear,0.95,0.9695121951219512,13.163034485340146,2.65801770920311,328
-rdflex,interacted cutoff and score,Linear,LGBM,0.9,0.9359756097560976,11.420715187719008,2.7600510207095925,328
-rdflex,interacted cutoff and score,Linear,LGBM,0.95,0.975609756097561,13.608621508228133,2.7600510207095925,328
-rdflex,interacted cutoff and score,Linear,Linear,0.9,0.9329268292682927,11.182065032541443,2.6678840377562207,328
-rdflex,interacted cutoff and score,Linear,Linear,0.95,0.9695121951219512,13.324252308811996,2.6678840377562207,328
-rdflex,interacted cutoff and score,Linear,Stacked,0.9,0.9207317073170732,11.179341833779677,2.737095486322336,328
-rdflex,interacted cutoff and score,Linear,Stacked,0.95,0.9725609756097561,13.321007417346669,2.737095486322336,328
-rdflex,interacted cutoff and score,Stacked,Global linear,0.9,0.9298780487804879,2.33175306213734,0.564578641351739,328
-rdflex,interacted cutoff and score,Stacked,Global linear,0.95,0.9725609756097561,2.778455145033404,0.564578641351739,328
-rdflex,interacted cutoff and score,Stacked,LGBM,0.9,0.9359756097560976,2.2561521994383473,0.5155050289769663,328
-rdflex,interacted cutoff and score,Stacked,LGBM,0.95,0.975609756097561,2.6883711608646683,0.5155050289769663,328
-rdflex,interacted cutoff and score,Stacked,Linear,0.9,0.9390243902439024,2.3456922453937534,0.5278125836408509,328
-rdflex,interacted cutoff and score,Stacked,Linear,0.95,0.9695121951219512,2.7950647063395415,0.5278125836408509,328
-rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.9420731707317073,2.330264554451441,0.5266693508368335,328
-rdflex,interacted cutoff and score,Stacked,Stacked,0.95,0.9817073170731707,2.7766814787282263,0.5266693508368335,328
-rdrobust,cutoff,linear,linear,0.9,0.926829268292683,10.913917661821893,2.6462280044256774,328
-rdrobust,cutoff,linear,linear,0.95,0.9695121951219512,13.004735009188504,2.6462280044256774,328
+rdflex,cutoff,Global linear,Global linear,0.9,0.9441860465116279,10.564078457114544,2.551067747184178,215
+rdflex,cutoff,Global linear,Global linear,0.95,0.9767441860465116,12.587875885451556,2.551067747184178,215
+rdflex,cutoff,Global linear,LGBM,0.9,0.9441860465116279,10.720818189894182,2.6193908666977097,215
+rdflex,cutoff,Global linear,LGBM,0.95,0.9813953488372092,12.77464279659847,2.6193908666977097,215
+rdflex,cutoff,Global linear,Linear,0.9,0.9395348837209302,10.70630439095184,2.600242702248606,215
+rdflex,cutoff,Global linear,Linear,0.95,0.9767441860465116,12.757348538471337,2.600242702248606,215
+rdflex,cutoff,Global linear,Stacked,0.9,0.9488372093023256,10.550901985463776,2.6245949134160043,215
+rdflex,cutoff,Global linear,Stacked,0.95,0.9720930232558139,12.572175151078808,2.6245949134160043,215
+rdflex,cutoff,LGBM,Global linear,0.9,0.9348837209302325,2.0297318211396234,0.4683467367083583,215
+rdflex,cutoff,LGBM,Global linear,0.95,0.9674418604651163,2.4185746394234777,0.4683467367083583,215
+rdflex,cutoff,LGBM,LGBM,0.9,0.9302325581395349,2.044586554471598,0.5043246741119822,215
+rdflex,cutoff,LGBM,LGBM,0.95,0.9720930232558139,2.4362751459327274,0.5043246741119822,215
+rdflex,cutoff,LGBM,Linear,0.9,0.9534883720930233,2.08203895053334,0.4855437858592723,215
+rdflex,cutoff,LGBM,Linear,0.95,0.9906976744186047,2.4809024283929855,0.4855437858592723,215
+rdflex,cutoff,LGBM,Stacked,0.9,0.9069767441860465,2.0198922945130877,0.4747442988206191,215
+rdflex,cutoff,LGBM,Stacked,0.95,0.9674418604651163,2.406850120294882,0.4747442988206191,215
+rdflex,cutoff,Linear,Global linear,0.9,0.9441860465116279,10.563314739120838,2.5435252785821545,215
+rdflex,cutoff,Linear,Global linear,0.95,0.9767441860465116,12.58696585933283,2.5435252785821545,215
+rdflex,cutoff,Linear,LGBM,0.9,0.9441860465116279,10.765215760853366,2.631659380451768,215
+rdflex,cutoff,Linear,LGBM,0.95,0.9767441860465116,12.827545765382592,2.631659380451768,215
+rdflex,cutoff,Linear,Linear,0.9,0.9348837209302325,10.756013581940026,2.606696901550894,215
+rdflex,cutoff,Linear,Linear,0.95,0.9767441860465116,12.816580692895947,2.606696901550894,215
+rdflex,cutoff,Linear,Stacked,0.9,0.9441860465116279,10.409664738957082,2.5039216623720044,215
+rdflex,cutoff,Linear,Stacked,0.95,0.9767441860465116,12.403880591676717,2.5039216623720044,215
+rdflex,cutoff,Stacked,Global linear,0.9,0.9302325581395349,2.1011994824527753,0.49868951518289967,215
+rdflex,cutoff,Stacked,Global linear,0.95,0.9720930232558139,2.503733610372579,0.49868951518289967,215
+rdflex,cutoff,Stacked,LGBM,0.9,0.9488372093023256,1.9950803384374163,0.4657168932997721,215
+rdflex,cutoff,Stacked,LGBM,0.95,0.9906976744186047,2.3772848510833984,0.4657168932997721,215
+rdflex,cutoff,Stacked,Linear,0.9,0.9395348837209302,2.1069969432360263,0.4532611529970158,215
+rdflex,cutoff,Stacked,Linear,0.95,0.9813953488372092,2.5106417109784758,0.4532611529970158,215
+rdflex,cutoff,Stacked,Stacked,0.9,0.9395348837209302,2.021493818181608,0.4459561817762452,215
+rdflex,cutoff,Stacked,Stacked,0.95,0.9720930232558139,2.4087584534494284,0.4459561817762452,215
+rdflex,cutoff and score,Global linear,Global linear,0.9,0.9441860465116279,10.555038490536257,2.5583707254574874,215
+rdflex,cutoff and score,Global linear,Global linear,0.95,0.9767441860465116,12.577104100883878,2.5583707254574874,215
+rdflex,cutoff and score,Global linear,LGBM,0.9,0.9441860465116279,10.814888659273302,2.631274042756371,215
+rdflex,cutoff and score,Global linear,LGBM,0.95,0.9813953488372092,12.886734674544819,2.631274042756371,215
+rdflex,cutoff and score,Global linear,Linear,0.9,0.9441860465116279,10.730361542844257,2.5946164225884303,215
+rdflex,cutoff and score,Global linear,Linear,0.95,0.9767441860465116,12.786014403024367,2.5946164225884303,215
+rdflex,cutoff and score,Global linear,Stacked,0.9,0.9488372093023256,10.856448636527878,2.632208009950369,215
+rdflex,cutoff and score,Global linear,Stacked,0.95,0.9767441860465116,12.936256441881794,2.632208009950369,215
+rdflex,cutoff and score,LGBM,Global linear,0.9,0.9534883720930233,2.154085713733332,0.4964064240462917,215
+rdflex,cutoff and score,LGBM,Global linear,0.95,0.9813953488372092,2.5667514418011774,0.4964064240462917,215
+rdflex,cutoff and score,LGBM,LGBM,0.9,0.9395348837209302,2.2019009446437523,0.5306846250687649,215
+rdflex,cutoff and score,LGBM,LGBM,0.95,0.9674418604651163,2.6237268035970964,0.5306846250687649,215
+rdflex,cutoff and score,LGBM,Linear,0.9,0.9441860465116279,2.1979998936772565,0.4777670441558015,215
+rdflex,cutoff and score,LGBM,Linear,0.95,0.9767441860465116,2.619078414663938,0.4777670441558015,215
+rdflex,cutoff and score,LGBM,Stacked,0.9,0.9627906976744186,2.1342811617871655,0.5086055446347446,215
+rdflex,cutoff and score,LGBM,Stacked,0.95,0.9813953488372092,2.5431528626276743,0.5086055446347446,215
+rdflex,cutoff and score,Linear,Global linear,0.9,0.9302325581395349,10.652621745052354,2.5911989762617416,215
+rdflex,cutoff and score,Linear,Global linear,0.95,0.9767441860465116,12.693381720492033,2.5911989762617416,215
+rdflex,cutoff and score,Linear,LGBM,0.9,0.9534883720930233,10.855522617706825,2.6935083395769217,215
+rdflex,cutoff and score,Linear,LGBM,0.95,0.986046511627907,12.935153022399033,2.6935083395769217,215
+rdflex,cutoff and score,Linear,Linear,0.9,0.9255813953488372,10.733205177022684,2.5807562027245763,215
+rdflex,cutoff and score,Linear,Linear,0.95,0.9767441860465116,12.78940280214001,2.5807562027245763,215
+rdflex,cutoff and score,Linear,Stacked,0.9,0.9348837209302325,10.783638658275121,2.6412165548347764,215
+rdflex,cutoff and score,Linear,Stacked,0.95,0.9720930232558139,12.849498001645971,2.6412165548347764,215
+rdflex,cutoff and score,Stacked,Global linear,0.9,0.9255813953488372,2.1787628454054633,0.49697762349222463,215
+rdflex,cutoff and score,Stacked,Global linear,0.95,0.9720930232558139,2.596156057826964,0.49697762349222463,215
+rdflex,cutoff and score,Stacked,LGBM,0.9,0.9488372093023256,2.152271849473143,0.4946011688457605,215
+rdflex,cutoff and score,Stacked,LGBM,0.95,0.9674418604651163,2.5645900892257494,0.4946011688457605,215
+rdflex,cutoff and score,Stacked,Linear,0.9,0.9441860465116279,2.2137093363435847,0.5011137415834573,215
+rdflex,cutoff and score,Stacked,Linear,0.95,0.9906976744186047,2.6377973701616777,0.5011137415834573,215
+rdflex,cutoff and score,Stacked,Stacked,0.9,0.958139534883721,2.25246564874298,0.4914891271491966,215
+rdflex,cutoff and score,Stacked,Stacked,0.95,0.9813953488372092,2.6839783647691933,0.4914891271491966,215
+rdflex,interacted cutoff and score,Global linear,Global linear,0.9,0.9441860465116279,10.54168709403785,2.5297534633913115,215
+rdflex,interacted cutoff and score,Global linear,Global linear,0.95,0.9767441860465116,12.561194930699116,2.5297534633913115,215
+rdflex,interacted cutoff and score,Global linear,LGBM,0.9,0.9488372093023256,10.897314012692101,2.654786412792657,215
+rdflex,interacted cutoff and score,Global linear,LGBM,0.95,0.9813953488372092,12.984950540970116,2.654786412792657,215
+rdflex,interacted cutoff and score,Global linear,Linear,0.9,0.9488372093023256,10.693008615343809,2.5781840369951174,215
+rdflex,interacted cutoff and score,Global linear,Linear,0.95,0.9767441860465116,12.7415056446653,2.5781840369951174,215
+rdflex,interacted cutoff and score,Global linear,Stacked,0.9,0.9441860465116279,10.568918924439206,2.5945870147380847,215
+rdflex,interacted cutoff and score,Global linear,Stacked,0.95,0.9720930232558139,12.593643658017598,2.5945870147380847,215
+rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.9395348837209302,2.1417105351021193,0.49568507124761235,215
+rdflex,interacted cutoff and score,LGBM,Global linear,0.95,0.9813953488372092,2.5520055069520198,0.49568507124761235,215
+rdflex,interacted cutoff and score,LGBM,LGBM,0.9,0.9441860465116279,2.246333487218926,0.5353485593923827,215
+rdflex,interacted cutoff and score,LGBM,LGBM,0.95,0.9813953488372092,2.676671443631898,0.5353485593923827,215
+rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.9302325581395349,2.2086934276037695,0.5225223346862156,215
+rdflex,interacted cutoff and score,LGBM,Linear,0.95,0.986046511627907,2.6318205462554696,0.5225223346862156,215
+rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.9441860465116279,2.1293349077193984,0.5245965712685183,215
+rdflex,interacted cutoff and score,LGBM,Stacked,0.95,0.986046511627907,2.5372590373824604,0.5245965712685183,215
+rdflex,interacted cutoff and score,Linear,Global linear,0.9,0.9348837209302325,10.68945615595058,2.6095743442616093,215
+rdflex,interacted cutoff and score,Linear,Global linear,0.95,0.9767441860465116,12.737272628211327,2.6095743442616093,215
+rdflex,interacted cutoff and score,Linear,LGBM,0.9,0.9488372093023256,11.103386119878946,2.736586139513755,215
+rdflex,interacted cutoff and score,Linear,LGBM,0.95,0.9813953488372092,13.230500601891379,2.736586139513755,215
+rdflex,interacted cutoff and score,Linear,Linear,0.9,0.9488372093023256,10.817474460477358,2.6161162830974765,215
+rdflex,interacted cutoff and score,Linear,Linear,0.95,0.9767441860465116,12.88981584672214,2.6161162830974765,215
+rdflex,interacted cutoff and score,Linear,Stacked,0.9,0.9302325581395349,10.751105193637315,2.6430978011159643,215
+rdflex,interacted cutoff and score,Linear,Stacked,0.95,0.9720930232558139,12.810731987492732,2.6430978011159643,215
+rdflex,interacted cutoff and score,Stacked,Global linear,0.9,0.9255813953488372,2.2292702611333306,0.5276588779763145,215
+rdflex,interacted cutoff and score,Stacked,Global linear,0.95,0.9720930232558139,2.6563393556941923,0.5276588779763145,215
+rdflex,interacted cutoff and score,Stacked,LGBM,0.9,0.9348837209302325,2.2109732075901007,0.5128601169070777,215
+rdflex,interacted cutoff and score,Stacked,LGBM,0.95,0.9767441860465116,2.634537071660934,0.5128601169070777,215
+rdflex,interacted cutoff and score,Stacked,Linear,0.9,0.9209302325581395,2.240667110472258,0.5118006538392077,215
+rdflex,interacted cutoff and score,Stacked,Linear,0.95,0.9674418604651163,2.6699195392895727,0.5118006538392077,215
+rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.9488372093023256,2.184127378703806,0.4849494916957177,215
+rdflex,interacted cutoff and score,Stacked,Stacked,0.95,0.986046511627907,2.6025482935167163,0.4849494916957177,215
+rdrobust,cutoff,linear,linear,0.9,0.9395348837209302,10.399421359617577,2.53931530408838,215
+rdrobust,cutoff,linear,linear,0.95,0.9720930232558139,12.39167485235958,2.53931530408838,215
diff --git a/results/rdd/rdd_fuzzy_coverage_metadata.csv b/results/rdd/rdd_fuzzy_coverage_metadata.csv
index ea8eaa3..54da4d8 100644
--- a/results/rdd/rdd_fuzzy_coverage_metadata.csv
+++ b/results/rdd/rdd_fuzzy_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_fuzzy_coverage.py,2024-12-02 19:02:59,19854.447350025177,3.12.7
+0.9.dev0,rdd_fuzzy_coverage.py,2025-01-06 18:16:59,19873.760499715805,3.12.8

From 93b528cdfe3fd514bd7d151907d4a3de534084f1 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Tue, 7 Jan 2025 14:09:39 +0000
Subject: [PATCH 30/58] Update results from script:
 scripts/rdd/rdd_sharp_coverage.py

---
 results/rdd/rdd_sharp_coverage_metadata.csv | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/results/rdd/rdd_sharp_coverage_metadata.csv b/results/rdd/rdd_sharp_coverage_metadata.csv
index 3fa91a4..1c63090 100644
--- a/results/rdd/rdd_sharp_coverage_metadata.csv
+++ b/results/rdd/rdd_sharp_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_sharp_coverage.py,2025-01-06 13:53:34,4068.1591482162476,3.12.8
+0.9.dev0,rdd_sharp_coverage.py,2025-01-07 14:09:39,4160.666923284531,3.12.8

From 5797755045f9009780890cfca33bd304eef65f1c Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Tue, 7 Jan 2025 18:31:43 +0000
Subject: [PATCH 31/58] Update results from script:
 scripts/rdd/rdd_fuzzy_coverage.py

---
 results/rdd/rdd_fuzzy_coverage.csv          | 196 ++++++++++----------
 results/rdd/rdd_fuzzy_coverage_metadata.csv |   2 +-
 2 files changed, 99 insertions(+), 99 deletions(-)

diff --git a/results/rdd/rdd_fuzzy_coverage.csv b/results/rdd/rdd_fuzzy_coverage.csv
index aae1460..2326df5 100644
--- a/results/rdd/rdd_fuzzy_coverage.csv
+++ b/results/rdd/rdd_fuzzy_coverage.csv
@@ -1,99 +1,99 @@
 Method,fs specification,Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-rdflex,cutoff,Global linear,Global linear,0.9,0.9441860465116279,10.564078457114544,2.551067747184178,215
-rdflex,cutoff,Global linear,Global linear,0.95,0.9767441860465116,12.587875885451556,2.551067747184178,215
-rdflex,cutoff,Global linear,LGBM,0.9,0.9441860465116279,10.720818189894182,2.6193908666977097,215
-rdflex,cutoff,Global linear,LGBM,0.95,0.9813953488372092,12.77464279659847,2.6193908666977097,215
-rdflex,cutoff,Global linear,Linear,0.9,0.9395348837209302,10.70630439095184,2.600242702248606,215
-rdflex,cutoff,Global linear,Linear,0.95,0.9767441860465116,12.757348538471337,2.600242702248606,215
-rdflex,cutoff,Global linear,Stacked,0.9,0.9488372093023256,10.550901985463776,2.6245949134160043,215
-rdflex,cutoff,Global linear,Stacked,0.95,0.9720930232558139,12.572175151078808,2.6245949134160043,215
-rdflex,cutoff,LGBM,Global linear,0.9,0.9348837209302325,2.0297318211396234,0.4683467367083583,215
-rdflex,cutoff,LGBM,Global linear,0.95,0.9674418604651163,2.4185746394234777,0.4683467367083583,215
-rdflex,cutoff,LGBM,LGBM,0.9,0.9302325581395349,2.044586554471598,0.5043246741119822,215
-rdflex,cutoff,LGBM,LGBM,0.95,0.9720930232558139,2.4362751459327274,0.5043246741119822,215
-rdflex,cutoff,LGBM,Linear,0.9,0.9534883720930233,2.08203895053334,0.4855437858592723,215
-rdflex,cutoff,LGBM,Linear,0.95,0.9906976744186047,2.4809024283929855,0.4855437858592723,215
-rdflex,cutoff,LGBM,Stacked,0.9,0.9069767441860465,2.0198922945130877,0.4747442988206191,215
-rdflex,cutoff,LGBM,Stacked,0.95,0.9674418604651163,2.406850120294882,0.4747442988206191,215
-rdflex,cutoff,Linear,Global linear,0.9,0.9441860465116279,10.563314739120838,2.5435252785821545,215
-rdflex,cutoff,Linear,Global linear,0.95,0.9767441860465116,12.58696585933283,2.5435252785821545,215
-rdflex,cutoff,Linear,LGBM,0.9,0.9441860465116279,10.765215760853366,2.631659380451768,215
-rdflex,cutoff,Linear,LGBM,0.95,0.9767441860465116,12.827545765382592,2.631659380451768,215
-rdflex,cutoff,Linear,Linear,0.9,0.9348837209302325,10.756013581940026,2.606696901550894,215
-rdflex,cutoff,Linear,Linear,0.95,0.9767441860465116,12.816580692895947,2.606696901550894,215
-rdflex,cutoff,Linear,Stacked,0.9,0.9441860465116279,10.409664738957082,2.5039216623720044,215
-rdflex,cutoff,Linear,Stacked,0.95,0.9767441860465116,12.403880591676717,2.5039216623720044,215
-rdflex,cutoff,Stacked,Global linear,0.9,0.9302325581395349,2.1011994824527753,0.49868951518289967,215
-rdflex,cutoff,Stacked,Global linear,0.95,0.9720930232558139,2.503733610372579,0.49868951518289967,215
-rdflex,cutoff,Stacked,LGBM,0.9,0.9488372093023256,1.9950803384374163,0.4657168932997721,215
-rdflex,cutoff,Stacked,LGBM,0.95,0.9906976744186047,2.3772848510833984,0.4657168932997721,215
-rdflex,cutoff,Stacked,Linear,0.9,0.9395348837209302,2.1069969432360263,0.4532611529970158,215
-rdflex,cutoff,Stacked,Linear,0.95,0.9813953488372092,2.5106417109784758,0.4532611529970158,215
-rdflex,cutoff,Stacked,Stacked,0.9,0.9395348837209302,2.021493818181608,0.4459561817762452,215
-rdflex,cutoff,Stacked,Stacked,0.95,0.9720930232558139,2.4087584534494284,0.4459561817762452,215
-rdflex,cutoff and score,Global linear,Global linear,0.9,0.9441860465116279,10.555038490536257,2.5583707254574874,215
-rdflex,cutoff and score,Global linear,Global linear,0.95,0.9767441860465116,12.577104100883878,2.5583707254574874,215
-rdflex,cutoff and score,Global linear,LGBM,0.9,0.9441860465116279,10.814888659273302,2.631274042756371,215
-rdflex,cutoff and score,Global linear,LGBM,0.95,0.9813953488372092,12.886734674544819,2.631274042756371,215
-rdflex,cutoff and score,Global linear,Linear,0.9,0.9441860465116279,10.730361542844257,2.5946164225884303,215
-rdflex,cutoff and score,Global linear,Linear,0.95,0.9767441860465116,12.786014403024367,2.5946164225884303,215
-rdflex,cutoff and score,Global linear,Stacked,0.9,0.9488372093023256,10.856448636527878,2.632208009950369,215
-rdflex,cutoff and score,Global linear,Stacked,0.95,0.9767441860465116,12.936256441881794,2.632208009950369,215
-rdflex,cutoff and score,LGBM,Global linear,0.9,0.9534883720930233,2.154085713733332,0.4964064240462917,215
-rdflex,cutoff and score,LGBM,Global linear,0.95,0.9813953488372092,2.5667514418011774,0.4964064240462917,215
-rdflex,cutoff and score,LGBM,LGBM,0.9,0.9395348837209302,2.2019009446437523,0.5306846250687649,215
-rdflex,cutoff and score,LGBM,LGBM,0.95,0.9674418604651163,2.6237268035970964,0.5306846250687649,215
-rdflex,cutoff and score,LGBM,Linear,0.9,0.9441860465116279,2.1979998936772565,0.4777670441558015,215
-rdflex,cutoff and score,LGBM,Linear,0.95,0.9767441860465116,2.619078414663938,0.4777670441558015,215
-rdflex,cutoff and score,LGBM,Stacked,0.9,0.9627906976744186,2.1342811617871655,0.5086055446347446,215
-rdflex,cutoff and score,LGBM,Stacked,0.95,0.9813953488372092,2.5431528626276743,0.5086055446347446,215
-rdflex,cutoff and score,Linear,Global linear,0.9,0.9302325581395349,10.652621745052354,2.5911989762617416,215
-rdflex,cutoff and score,Linear,Global linear,0.95,0.9767441860465116,12.693381720492033,2.5911989762617416,215
-rdflex,cutoff and score,Linear,LGBM,0.9,0.9534883720930233,10.855522617706825,2.6935083395769217,215
-rdflex,cutoff and score,Linear,LGBM,0.95,0.986046511627907,12.935153022399033,2.6935083395769217,215
-rdflex,cutoff and score,Linear,Linear,0.9,0.9255813953488372,10.733205177022684,2.5807562027245763,215
-rdflex,cutoff and score,Linear,Linear,0.95,0.9767441860465116,12.78940280214001,2.5807562027245763,215
-rdflex,cutoff and score,Linear,Stacked,0.9,0.9348837209302325,10.783638658275121,2.6412165548347764,215
-rdflex,cutoff and score,Linear,Stacked,0.95,0.9720930232558139,12.849498001645971,2.6412165548347764,215
-rdflex,cutoff and score,Stacked,Global linear,0.9,0.9255813953488372,2.1787628454054633,0.49697762349222463,215
-rdflex,cutoff and score,Stacked,Global linear,0.95,0.9720930232558139,2.596156057826964,0.49697762349222463,215
-rdflex,cutoff and score,Stacked,LGBM,0.9,0.9488372093023256,2.152271849473143,0.4946011688457605,215
-rdflex,cutoff and score,Stacked,LGBM,0.95,0.9674418604651163,2.5645900892257494,0.4946011688457605,215
-rdflex,cutoff and score,Stacked,Linear,0.9,0.9441860465116279,2.2137093363435847,0.5011137415834573,215
-rdflex,cutoff and score,Stacked,Linear,0.95,0.9906976744186047,2.6377973701616777,0.5011137415834573,215
-rdflex,cutoff and score,Stacked,Stacked,0.9,0.958139534883721,2.25246564874298,0.4914891271491966,215
-rdflex,cutoff and score,Stacked,Stacked,0.95,0.9813953488372092,2.6839783647691933,0.4914891271491966,215
-rdflex,interacted cutoff and score,Global linear,Global linear,0.9,0.9441860465116279,10.54168709403785,2.5297534633913115,215
-rdflex,interacted cutoff and score,Global linear,Global linear,0.95,0.9767441860465116,12.561194930699116,2.5297534633913115,215
-rdflex,interacted cutoff and score,Global linear,LGBM,0.9,0.9488372093023256,10.897314012692101,2.654786412792657,215
-rdflex,interacted cutoff and score,Global linear,LGBM,0.95,0.9813953488372092,12.984950540970116,2.654786412792657,215
-rdflex,interacted cutoff and score,Global linear,Linear,0.9,0.9488372093023256,10.693008615343809,2.5781840369951174,215
-rdflex,interacted cutoff and score,Global linear,Linear,0.95,0.9767441860465116,12.7415056446653,2.5781840369951174,215
-rdflex,interacted cutoff and score,Global linear,Stacked,0.9,0.9441860465116279,10.568918924439206,2.5945870147380847,215
-rdflex,interacted cutoff and score,Global linear,Stacked,0.95,0.9720930232558139,12.593643658017598,2.5945870147380847,215
-rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.9395348837209302,2.1417105351021193,0.49568507124761235,215
-rdflex,interacted cutoff and score,LGBM,Global linear,0.95,0.9813953488372092,2.5520055069520198,0.49568507124761235,215
-rdflex,interacted cutoff and score,LGBM,LGBM,0.9,0.9441860465116279,2.246333487218926,0.5353485593923827,215
-rdflex,interacted cutoff and score,LGBM,LGBM,0.95,0.9813953488372092,2.676671443631898,0.5353485593923827,215
-rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.9302325581395349,2.2086934276037695,0.5225223346862156,215
-rdflex,interacted cutoff and score,LGBM,Linear,0.95,0.986046511627907,2.6318205462554696,0.5225223346862156,215
-rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.9441860465116279,2.1293349077193984,0.5245965712685183,215
-rdflex,interacted cutoff and score,LGBM,Stacked,0.95,0.986046511627907,2.5372590373824604,0.5245965712685183,215
-rdflex,interacted cutoff and score,Linear,Global linear,0.9,0.9348837209302325,10.68945615595058,2.6095743442616093,215
-rdflex,interacted cutoff and score,Linear,Global linear,0.95,0.9767441860465116,12.737272628211327,2.6095743442616093,215
-rdflex,interacted cutoff and score,Linear,LGBM,0.9,0.9488372093023256,11.103386119878946,2.736586139513755,215
-rdflex,interacted cutoff and score,Linear,LGBM,0.95,0.9813953488372092,13.230500601891379,2.736586139513755,215
-rdflex,interacted cutoff and score,Linear,Linear,0.9,0.9488372093023256,10.817474460477358,2.6161162830974765,215
-rdflex,interacted cutoff and score,Linear,Linear,0.95,0.9767441860465116,12.88981584672214,2.6161162830974765,215
-rdflex,interacted cutoff and score,Linear,Stacked,0.9,0.9302325581395349,10.751105193637315,2.6430978011159643,215
-rdflex,interacted cutoff and score,Linear,Stacked,0.95,0.9720930232558139,12.810731987492732,2.6430978011159643,215
-rdflex,interacted cutoff and score,Stacked,Global linear,0.9,0.9255813953488372,2.2292702611333306,0.5276588779763145,215
-rdflex,interacted cutoff and score,Stacked,Global linear,0.95,0.9720930232558139,2.6563393556941923,0.5276588779763145,215
-rdflex,interacted cutoff and score,Stacked,LGBM,0.9,0.9348837209302325,2.2109732075901007,0.5128601169070777,215
-rdflex,interacted cutoff and score,Stacked,LGBM,0.95,0.9767441860465116,2.634537071660934,0.5128601169070777,215
-rdflex,interacted cutoff and score,Stacked,Linear,0.9,0.9209302325581395,2.240667110472258,0.5118006538392077,215
-rdflex,interacted cutoff and score,Stacked,Linear,0.95,0.9674418604651163,2.6699195392895727,0.5118006538392077,215
-rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.9488372093023256,2.184127378703806,0.4849494916957177,215
-rdflex,interacted cutoff and score,Stacked,Stacked,0.95,0.986046511627907,2.6025482935167163,0.4849494916957177,215
-rdrobust,cutoff,linear,linear,0.9,0.9395348837209302,10.399421359617577,2.53931530408838,215
-rdrobust,cutoff,linear,linear,0.95,0.9720930232558139,12.39167485235958,2.53931530408838,215
+rdflex,cutoff,Global linear,Global linear,0.9,0.9439252336448598,10.555050121998914,2.557454881202291,214
+rdflex,cutoff,Global linear,Global linear,0.95,0.9766355140186916,12.577117960626483,2.557454881202291,214
+rdflex,cutoff,Global linear,LGBM,0.9,0.9439252336448598,10.714048740732457,2.6261561018337476,214
+rdflex,cutoff,Global linear,LGBM,0.95,0.9813084112149533,12.766576500403625,2.6261561018337476,214
+rdflex,cutoff,Global linear,Linear,0.9,0.9392523364485982,10.69861124776851,2.6084394390564283,214
+rdflex,cutoff,Global linear,Linear,0.95,0.9766355140186916,12.748181592963135,2.6084394390564283,214
+rdflex,cutoff,Global linear,Stacked,0.9,0.9485981308411215,10.542991289273992,2.6322225801086323,214
+rdflex,cutoff,Global linear,Stacked,0.95,0.9719626168224299,12.562748975174422,2.6322225801086323,214
+rdflex,cutoff,LGBM,Global linear,0.9,0.9345794392523364,2.029337501353004,0.4700006325418856,214
+rdflex,cutoff,LGBM,Global linear,0.95,0.9672897196261683,2.4181047784173058,0.4700006325418856,214
+rdflex,cutoff,LGBM,LGBM,0.9,0.9299065420560748,2.0440609614236096,0.5062048055000609,214
+rdflex,cutoff,LGBM,LGBM,0.95,0.9719626168224299,2.4356488631877444,0.5062048055000609,214
+rdflex,cutoff,LGBM,Linear,0.9,0.9532710280373832,2.082858834410821,0.4862344864688502,214
+rdflex,cutoff,LGBM,Linear,0.95,0.9906542056074766,2.481879380290126,0.4862344864688502,214
+rdflex,cutoff,LGBM,Stacked,0.9,0.9065420560747663,2.019090300402747,0.47574061346930346,214
+rdflex,cutoff,LGBM,Stacked,0.95,0.9672897196261683,2.4058944853700925,0.47574061346930346,214
+rdflex,cutoff,Linear,Global linear,0.9,0.9439252336448598,10.55612712298056,2.5518911139757785,214
+rdflex,cutoff,Linear,Global linear,0.95,0.9766355140186916,12.578401286449983,2.5518911139757785,214
+rdflex,cutoff,Linear,LGBM,0.9,0.9439252336448598,10.761495324878737,2.639346775020516,214
+rdflex,cutoff,Linear,LGBM,0.95,0.9766355140186916,12.823112592486487,2.639346775020516,214
+rdflex,cutoff,Linear,Linear,0.9,0.9345794392523364,10.748611527983986,2.614648978480689,214
+rdflex,cutoff,Linear,Linear,0.95,0.9766355140186916,12.807760601595577,2.614648978480689,214
+rdflex,cutoff,Linear,Stacked,0.9,0.9439252336448598,10.400228114739594,2.5119733327212943,214
+rdflex,cutoff,Linear,Stacked,0.95,0.9766355140186916,12.392636160379698,2.5119733327212943,214
+rdflex,cutoff,Stacked,Global linear,0.9,0.9299065420560748,2.100352405285733,0.4993647885601086,214
+rdflex,cutoff,Stacked,Global linear,0.95,0.9719626168224299,2.502724255672364,0.4993647885601086,214
+rdflex,cutoff,Stacked,LGBM,0.9,0.9485981308411215,1.9952932413270021,0.4654367817416753,214
+rdflex,cutoff,Stacked,LGBM,0.95,0.9906542056074766,2.3775385405235743,0.4654367817416753,214
+rdflex,cutoff,Stacked,Linear,0.9,0.9392523364485982,2.1078303244900973,0.45375955245086014,214
+rdflex,cutoff,Stacked,Linear,0.95,0.9813084112149533,2.5116347459918087,0.45375955245086014,214
+rdflex,cutoff,Stacked,Stacked,0.9,0.9392523364485982,2.0202332872592588,0.4453107509428898,214
+rdflex,cutoff,Stacked,Stacked,0.95,0.9719626168224299,2.407256438213105,0.4453107509428898,214
+rdflex,cutoff and score,Global linear,Global linear,0.9,0.9439252336448598,10.545901405614005,2.5648476809096707,214
+rdflex,cutoff and score,Global linear,Global linear,0.95,0.9766355140186916,12.56621659267168,2.5648476809096707,214
+rdflex,cutoff and score,Global linear,LGBM,0.9,0.9439252336448598,10.795739229679457,2.6380721682853405,214
+rdflex,cutoff and score,Global linear,LGBM,0.95,0.9813084112149533,12.863916721802127,2.6380721682853405,214
+rdflex,cutoff and score,Global linear,Linear,0.9,0.9439252336448598,10.722039462420188,2.601946990911434,214
+rdflex,cutoff and score,Global linear,Linear,0.95,0.9766355140186916,12.776098032570266,2.601946990911434,214
+rdflex,cutoff and score,Global linear,Stacked,0.9,0.9485981308411215,10.84957752003617,2.6393360419176215,214
+rdflex,cutoff and score,Global linear,Stacked,0.95,0.9766355140186916,12.928069001591265,2.6393360419176215,214
+rdflex,cutoff and score,LGBM,Global linear,0.9,0.9532710280373832,2.1553015781124825,0.4985124204199334,214
+rdflex,cutoff and score,LGBM,Global linear,0.95,0.9813084112149533,2.5682002335685254,0.4985124204199334,214
+rdflex,cutoff and score,LGBM,LGBM,0.9,0.9392523364485982,2.1973662757190073,0.5327660380926273,214
+rdflex,cutoff and score,LGBM,LGBM,0.95,0.9672897196261683,2.6183234122991212,0.5327660380926273,214
+rdflex,cutoff and score,LGBM,Linear,0.9,0.9439252336448598,2.198701801510649,0.478151037013903,214
+rdflex,cutoff and score,LGBM,Linear,0.95,0.9766355140186916,2.619914789433933,0.478151037013903,214
+rdflex,cutoff and score,LGBM,Stacked,0.9,0.9626168224299065,2.1339233144534187,0.5089928094483224,214
+rdflex,cutoff and score,LGBM,Stacked,0.95,0.9813084112149533,2.542726461229631,0.5089928094483224,214
+rdflex,cutoff and score,Linear,Global linear,0.9,0.9299065420560748,10.644692713092242,2.598861379899407,214
+rdflex,cutoff and score,Linear,Global linear,0.95,0.9766355140186916,12.683933696169714,2.598861379899407,214
+rdflex,cutoff and score,Linear,LGBM,0.9,0.9532710280373832,10.854187936587056,2.7014940383227355,214
+rdflex,cutoff and score,Linear,LGBM,0.95,0.985981308411215,12.933562651752837,2.7014940383227355,214
+rdflex,cutoff and score,Linear,Linear,0.9,0.9252336448598131,10.724343356023862,2.5881292715569817,214
+rdflex,cutoff and score,Linear,Linear,0.95,0.9766355140186916,12.77884329112302,2.5881292715569817,214
+rdflex,cutoff and score,Linear,Stacked,0.9,0.9345794392523364,10.776895897775766,2.6499533364372025,214
+rdflex,cutoff and score,Linear,Stacked,0.95,0.9719626168224299,12.841463506953815,2.6499533364372025,214
+rdflex,cutoff and score,Stacked,Global linear,0.9,0.9252336448598131,2.1786088679569744,0.4966485703629167,214
+rdflex,cutoff and score,Stacked,Global linear,0.95,0.9719626168224299,2.5959725823805626,0.4966485703629167,214
+rdflex,cutoff and score,Stacked,LGBM,0.9,0.9485981308411215,2.1461144187284016,0.4942766032999762,214
+rdflex,cutoff and score,Stacked,LGBM,0.95,0.9672897196261683,2.557253057954851,0.4942766032999762,214
+rdflex,cutoff and score,Stacked,Linear,0.9,0.9439252336448598,2.213911931815932,0.5031341173016854,214
+rdflex,cutoff and score,Stacked,Linear,0.95,0.9906542056074766,2.638038777556674,0.5031341173016854,214
+rdflex,cutoff and score,Stacked,Stacked,0.9,0.9579439252336449,2.2524280242253742,0.49230022385126054,214
+rdflex,cutoff and score,Stacked,Stacked,0.95,0.9813084112149533,2.683933532391263,0.49230022385126054,214
+rdflex,interacted cutoff and score,Global linear,Global linear,0.9,0.9439252336448598,10.533084606204715,2.536539354378303,214
+rdflex,interacted cutoff and score,Global linear,Global linear,0.95,0.9766355140186916,12.550944434208654,2.536539354378303,214
+rdflex,interacted cutoff and score,Global linear,LGBM,0.9,0.9485981308411215,10.889767355232552,2.662636398748481,214
+rdflex,interacted cutoff and score,Global linear,LGBM,0.95,0.9813084112149533,12.975958143967722,2.662636398748481,214
+rdflex,interacted cutoff and score,Global linear,Linear,0.9,0.9485981308411215,10.68507130374861,2.586187139044067,214
+rdflex,interacted cutoff and score,Global linear,Linear,0.95,0.9766355140186916,12.732047754549267,2.586187139044067,214
+rdflex,interacted cutoff and score,Global linear,Stacked,0.9,0.9439252336448598,10.558833608328598,2.603031338515077,214
+rdflex,interacted cutoff and score,Global linear,Stacked,0.95,0.9719626168224299,12.581626262654503,2.603031338515077,214
+rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.9392523364485982,2.142350464078299,0.4962040631698678,214
+rdflex,interacted cutoff and score,LGBM,Global linear,0.95,0.9813084112149533,2.5527680293585275,0.4962040631698678,214
+rdflex,interacted cutoff and score,LGBM,LGBM,0.9,0.9439252336448598,2.248059401902932,0.5371172689574487,214
+rdflex,interacted cutoff and score,LGBM,LGBM,0.95,0.9813084112149533,2.6787279978234766,0.5371172689574487,214
+rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.9299065420560748,2.2069200480948767,0.5204804556154995,214
+rdflex,interacted cutoff and score,LGBM,Linear,0.95,0.985981308411215,2.6297074342366247,0.5204804556154995,214
+rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.9439252336448598,2.1299774006239818,0.5255852225079005,214
+rdflex,interacted cutoff and score,LGBM,Stacked,0.95,0.985981308411215,2.5380246148980956,0.5255852225079005,214
+rdflex,interacted cutoff and score,Linear,Global linear,0.9,0.9345794392523364,10.68120559444222,2.6167228434568193,214
+rdflex,interacted cutoff and score,Linear,Global linear,0.95,0.9766355140186916,12.727441477801555,2.6167228434568193,214
+rdflex,interacted cutoff and score,Linear,LGBM,0.9,0.9485981308411215,11.082779264157297,2.7433028249989375,214
+rdflex,interacted cutoff and score,Linear,LGBM,0.95,0.9813084112149533,13.20594601880431,2.7433028249989375,214
+rdflex,interacted cutoff and score,Linear,Linear,0.9,0.9485981308411215,10.809863394765074,2.6250927449346375,214
+rdflex,interacted cutoff and score,Linear,Linear,0.95,0.9766355140186916,12.880746702552946,2.6250927449346375,214
+rdflex,interacted cutoff and score,Linear,Stacked,0.9,0.9299065420560748,10.73548376747478,2.6509536853647253,214
+rdflex,interacted cutoff and score,Linear,Stacked,0.95,0.9719626168224299,12.792117910128006,2.6509536853647253,214
+rdflex,interacted cutoff and score,Stacked,Global linear,0.9,0.9252336448598131,2.2291515095999177,0.5287095718263444,214
+rdflex,interacted cutoff and score,Stacked,Global linear,0.95,0.9719626168224299,2.6561978545145224,0.5287095718263444,214
+rdflex,interacted cutoff and score,Stacked,LGBM,0.9,0.9345794392523364,2.2108654801861354,0.5143407932379643,214
+rdflex,interacted cutoff and score,Stacked,LGBM,0.95,0.9766355140186916,2.634408706541716,0.5143407932379643,214
+rdflex,interacted cutoff and score,Stacked,Linear,0.9,0.9205607476635514,2.240692460872586,0.5126956666505772,214
+rdflex,interacted cutoff and score,Stacked,Linear,0.95,0.9672897196261683,2.6699497461546833,0.5126956666505772,214
+rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.9485981308411215,2.182225992342746,0.484470066239434,214
+rdflex,interacted cutoff and score,Stacked,Stacked,0.95,0.985981308411215,2.6002826519256894,0.484470066239434,214
+rdrobust,cutoff,linear,linear,0.9,0.9392523364485982,10.39225703260292,2.5469407480913575,214
+rdrobust,cutoff,linear,linear,0.95,0.9719626168224299,12.383138030181538,2.5469407480913575,214
diff --git a/results/rdd/rdd_fuzzy_coverage_metadata.csv b/results/rdd/rdd_fuzzy_coverage_metadata.csv
index 54da4d8..3322990 100644
--- a/results/rdd/rdd_fuzzy_coverage_metadata.csv
+++ b/results/rdd/rdd_fuzzy_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_fuzzy_coverage.py,2025-01-06 18:16:59,19873.760499715805,3.12.8
+0.9.dev0,rdd_fuzzy_coverage.py,2025-01-07 18:31:42,19889.126134634018,3.12.8

From 306b0b14d1db793248442db47e41a6487402b3c4 Mon Sep 17 00:00:00 2001
From: SvenKlaassen <sven.klaassen@uni-hamburg.de>
Date: Wed, 8 Jan 2025 13:13:17 +0100
Subject: [PATCH 32/58] update workflows and requirements for optional rdd

---
 .github/workflows/apo_sim.yml   | 3 ++-
 .github/workflows/did_sim.yml   | 3 ++-
 .github/workflows/iivm_sim.yml  | 3 ++-
 .github/workflows/irm_sim.yml   | 3 ++-
 .github/workflows/pliv_sim.yml  | 3 ++-
 .github/workflows/plr_sim.yml   | 1 +
 .github/workflows/quant_sim.yml | 3 ++-
 .github/workflows/rdd_sim.yml   | 3 ++-
 .github/workflows/ssm_sim.yml   | 3 ++-
 requirements.txt                | 2 +-
 10 files changed, 18 insertions(+), 9 deletions(-)

diff --git a/.github/workflows/apo_sim.yml b/.github/workflows/apo_sim.yml
index 1284d2a..1cbdc3f 100644
--- a/.github/workflows/apo_sim.yml
+++ b/.github/workflows/apo_sim.yml
@@ -59,7 +59,8 @@ jobs:
 
     - name: Install DoubleML from correct branch
       run: |
-        pip install git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}
+        pip uninstall -y doubleml
+        pip install "doubleml @ git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}"
 
     - name: Set up Git configuration
       run: |
diff --git a/.github/workflows/did_sim.yml b/.github/workflows/did_sim.yml
index c1ca6df..75c3ffc 100644
--- a/.github/workflows/did_sim.yml
+++ b/.github/workflows/did_sim.yml
@@ -60,7 +60,8 @@ jobs:
 
     - name: Install DoubleML from correct branch
       run: |
-        pip install git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}
+        pip uninstall -y doubleml
+        pip install "doubleml @ git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}"
 
     - name: Set up Git configuration
       run: |
diff --git a/.github/workflows/iivm_sim.yml b/.github/workflows/iivm_sim.yml
index 87aacf0..327962c 100644
--- a/.github/workflows/iivm_sim.yml
+++ b/.github/workflows/iivm_sim.yml
@@ -59,7 +59,8 @@ jobs:
 
     - name: Install DoubleML from correct branch
       run: |
-        pip install git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}
+        pip uninstall -y doubleml
+        pip install "doubleml @ git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}"
 
     - name: Set up Git configuration
       run: |
diff --git a/.github/workflows/irm_sim.yml b/.github/workflows/irm_sim.yml
index 813d942..63f5f55 100644
--- a/.github/workflows/irm_sim.yml
+++ b/.github/workflows/irm_sim.yml
@@ -64,7 +64,8 @@ jobs:
 
     - name: Install DoubleML from correct branch
       run: |
-        pip install git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}
+        pip uninstall -y doubleml
+        pip install "doubleml @ git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}"
 
     - name: Set up Git configuration
       run: |
diff --git a/.github/workflows/pliv_sim.yml b/.github/workflows/pliv_sim.yml
index eeb30a1..9c6921e 100644
--- a/.github/workflows/pliv_sim.yml
+++ b/.github/workflows/pliv_sim.yml
@@ -59,7 +59,8 @@ jobs:
 
     - name: Install DoubleML from correct branch
       run: |
-        pip install git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}
+        pip uninstall -y doubleml
+        pip install "doubleml @ git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}"
 
     - name: Set up Git configuration
       run: |
diff --git a/.github/workflows/plr_sim.yml b/.github/workflows/plr_sim.yml
index 5c02113..7d95d3c 100644
--- a/.github/workflows/plr_sim.yml
+++ b/.github/workflows/plr_sim.yml
@@ -62,6 +62,7 @@ jobs:
 
     - name: Install DoubleML from correct branch
       run: |
+        pip uninstall -y doubleml
         pip install git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}
 
     - name: Set up Git configuration
diff --git a/.github/workflows/quant_sim.yml b/.github/workflows/quant_sim.yml
index 931b1d2..af1ef7f 100644
--- a/.github/workflows/quant_sim.yml
+++ b/.github/workflows/quant_sim.yml
@@ -61,7 +61,8 @@ jobs:
 
     - name: Install DoubleML from correct branch
       run: |
-        pip install git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}
+        pip uninstall -y doubleml
+        pip install "doubleml @ git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}"
 
     - name: Set up Git configuration
       run: |
diff --git a/.github/workflows/rdd_sim.yml b/.github/workflows/rdd_sim.yml
index 13b64ee..533a6c6 100644
--- a/.github/workflows/rdd_sim.yml
+++ b/.github/workflows/rdd_sim.yml
@@ -60,7 +60,8 @@ jobs:
 
     - name: Install DoubleML from correct branch
       run: |
-        pip install git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}
+        pip uninstall -y doubleml
+        pip install "doubleml[rdd] @ git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}"
 
     - name: Install RDFlex from main branch
       run: |
diff --git a/.github/workflows/ssm_sim.yml b/.github/workflows/ssm_sim.yml
index cc2bdb7..e5a7474 100644
--- a/.github/workflows/ssm_sim.yml
+++ b/.github/workflows/ssm_sim.yml
@@ -60,7 +60,8 @@ jobs:
 
     - name: Install DoubleML from correct branch
       run: |
-        pip install git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}
+        pip uninstall -y doubleml
+        pip install "doubleml @ git+https://github.com/DoubleML/doubleml-for-py@${{ env.DML_BRANCH }}"
 
     - name: Set up Git configuration
       run: |
diff --git a/requirements.txt b/requirements.txt
index a58fef6..2accaab 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,4 +1,4 @@
-doubleml
+doubleml[rdd]
 joblib
 numpy
 pandas

From aaf76a644d7328d9889e8a09bff899f11309f522 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 13:02:48 +0000
Subject: [PATCH 33/58] Update results from script:
 scripts/plm/plr_gate_coverage.py

---
 results/plm/plr_gate_coverage_metadata.csv | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/results/plm/plr_gate_coverage_metadata.csv b/results/plm/plr_gate_coverage_metadata.csv
index ee21361..febe93f 100644
--- a/results/plm/plr_gate_coverage_metadata.csv
+++ b/results/plm/plr_gate_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,plr_gate_coverage.py,2024-09-09 08:15:54,3140.6088807582855,3.12.5
+0.10.dev0,plr_gate_coverage.py,2025-01-08 13:02:47,2835.5379569530487,3.12.8

From 2f501d6f789705e56dfa963ba53a9e6e39264a8b Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 13:08:54 +0000
Subject: [PATCH 34/58] Update results from script:
 scripts/rdd/rdd_sharp_coverage.py

---
 results/rdd/rdd_sharp_coverage_metadata.csv | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/results/rdd/rdd_sharp_coverage_metadata.csv b/results/rdd/rdd_sharp_coverage_metadata.csv
index 1c63090..8e3ce8d 100644
--- a/results/rdd/rdd_sharp_coverage_metadata.csv
+++ b/results/rdd/rdd_sharp_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_sharp_coverage.py,2025-01-07 14:09:39,4160.666923284531,3.12.8
+0.9.dev0,rdd_sharp_coverage.py,2025-01-08 13:08:54,4129.017676591873,3.12.8

From 63c068cb5975f9ae35c653ae6326cbe9e2dd9c64 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 13:08:06 +0000
Subject: [PATCH 35/58] Update results from script:
 scripts/irm/irm_gate_coverage.py

---
 results/irm/irm_gate_coverage.csv          | 8 ++++----
 results/irm/irm_gate_coverage_metadata.csv | 2 +-
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/results/irm/irm_gate_coverage.csv b/results/irm/irm_gate_coverage.csv
index f9fe660..f5dde96 100644
--- a/results/irm/irm_gate_coverage.csv
+++ b/results/irm/irm_gate_coverage.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
 LGBM,LGBM,0.9,0.941,2.1611526373873855,0.48511146422993706,1.0,5.063646757352436,1000
 LGBM,LGBM,0.95,0.9766666666666667,2.5751722007164304,0.48511146422993706,1.0,5.085406768554818,1000
-LGBM,Logistic Regression,0.9,0.916,0.39042806875814784,0.08854865701618221,0.997,0.9186129412168422,1000
-LGBM,Logistic Regression,0.95,0.9606666666666667,0.4652237383199531,0.08854865701618221,0.998,0.9197763724365766,1000
+LGBM,Logistic Regression,0.9,0.916,0.3904280687581478,0.08854865701618204,0.997,0.9186129412168421,1000
+LGBM,Logistic Regression,0.95,0.9606666666666667,0.4652237383199531,0.08854865701618204,0.998,0.9197763724365766,1000
 Lasso,LGBM,0.9,0.9043333333333333,2.047596498760145,0.49693265710872336,1.0,4.807194790243196,1000
 Lasso,LGBM,0.95,0.959,2.43986171576749,0.49693265710872336,1.0,4.819825928994352,1000
-Lasso,Logistic Regression,0.9,0.9173333333333333,0.4009671672064071,0.08997238623406144,0.999,0.9416356317140333,1000
-Lasso,Logistic Regression,0.95,0.9603333333333334,0.47778184868895535,0.08997238623406144,0.999,0.9403831822862943,1000
+Lasso,Logistic Regression,0.9,0.9173333333333333,0.400967167206407,0.08997238623406502,0.999,0.9416356317140329,1000
+Lasso,Logistic Regression,0.95,0.9603333333333334,0.4777818486889552,0.08997238623406502,0.999,0.9403831822862944,1000
diff --git a/results/irm/irm_gate_coverage_metadata.csv b/results/irm/irm_gate_coverage_metadata.csv
index 3e1d4f2..b7034be 100644
--- a/results/irm/irm_gate_coverage_metadata.csv
+++ b/results/irm/irm_gate_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,irm_gate_coverage.py,2024-09-09 08:26:21,3764.0360503196716,3.12.5
+0.10.dev0,irm_gate_coverage.py,2025-01-08 13:08:04,3153.3980271816254,3.12.8

From 007dd0755c4924001eaf24e90c03c4edeabe6956 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 13:14:11 +0000
Subject: [PATCH 36/58] Update results from script:
 scripts/irm/irm_atte_coverage.py

---
 results/irm/irm_atte_coverage.csv          | 16 ++++++++--------
 results/irm/irm_atte_coverage_metadata.csv |  2 +-
 2 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/results/irm/irm_atte_coverage.csv b/results/irm/irm_atte_coverage.csv
index 7c43c9f..3f486c5 100644
--- a/results/irm/irm_atte_coverage.csv
+++ b/results/irm/irm_atte_coverage.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-Lasso,Logistic Regression,0.9,0.888,0.5331759172799809,0.13451159762471473,1000
-Lasso,Logistic Regression,0.95,0.941,0.6353182910443254,0.13451159762471473,1000
-Lasso,Random Forest,0.9,0.893,0.7302574772345878,0.179721833597512,1000
-Lasso,Random Forest,0.95,0.956,0.8701554541807854,0.179721833597512,1000
-Random Forest,Logistic Regression,0.9,0.869,0.5521000550346591,0.15039777848508581,1000
-Random Forest,Logistic Regression,0.95,0.922,0.6578677920028921,0.15039777848508581,1000
-Random Forest,Random Forest,0.9,0.902,0.7520609787305578,0.18190144421857504,1000
-Random Forest,Random Forest,0.95,0.945,0.8961359286550816,0.18190144421857504,1000
+Lasso,Logistic Regression,0.9,0.887,0.5331759172799809,0.13448723008182129,1000
+Lasso,Logistic Regression,0.95,0.942,0.6353182910443254,0.13448723008182129,1000
+Lasso,Random Forest,0.9,0.895,0.7320685495582887,0.18096827990713532,1000
+Lasso,Random Forest,0.95,0.948,0.8723134799586961,0.18096827990713532,1000
+Random Forest,Logistic Regression,0.9,0.871,0.5508997607447915,0.1495507044107987,1000
+Random Forest,Logistic Regression,0.95,0.928,0.6564375531412434,0.1495507044107987,1000
+Random Forest,Random Forest,0.9,0.901,0.7500491227406757,0.18282767194851973,1000
+Random Forest,Random Forest,0.95,0.948,0.8937386543823805,0.18282767194851973,1000
diff --git a/results/irm/irm_atte_coverage_metadata.csv b/results/irm/irm_atte_coverage_metadata.csv
index b9f90c7..18af13a 100644
--- a/results/irm/irm_atte_coverage_metadata.csv
+++ b/results/irm/irm_atte_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,irm_atte_coverage.py,2024-09-09 08:23:18,3582.4482469558716,3.12.5
+0.10.dev0,irm_atte_coverage.py,2025-01-08 13:14:10,3538.650551557541,3.12.8

From 046da923670d6492eefe82021d9e8390957ada79 Mon Sep 17 00:00:00 2001
From: SvenKlaassen <sven.klaassen@uni-hamburg.de>
Date: Wed, 8 Jan 2025 14:19:01 +0100
Subject: [PATCH 37/58] fix typos

---
 doc/ssm/ssm_mar.qmd          | 2 +-
 doc/ssm/ssm_nonignorable.qmd | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/doc/ssm/ssm_mar.qmd b/doc/ssm/ssm_mar.qmd
index 1a7e033..0d52537 100644
--- a/doc/ssm/ssm_mar.qmd
+++ b/doc/ssm/ssm_mar.qmd
@@ -62,7 +62,7 @@ def make_pretty(df, level, n_rep):
 
 ## ATE Coverage
 
-The simulations are based on the  the [make_ssm_data](https://docs.doubleml.org/stable/api/generated/doubleml.datasets.make_ssm_data.html)-DGP with $500$ observations. The simulation considers data under [missingness at random](https://docs.doubleml.org/stable/guide/models.html#missingness-at-random).
+The simulations are based on the [make_ssm_data](https://docs.doubleml.org/stable/api/generated/doubleml.datasets.make_ssm_data.html)-DGP with $500$ observations. The simulation considers data under [missingness at random](https://docs.doubleml.org/stable/guide/models.html#missingness-at-random).
 
 ::: {.callout-note title="Metadata"  collapse="true"}
 
diff --git a/doc/ssm/ssm_nonignorable.qmd b/doc/ssm/ssm_nonignorable.qmd
index 44c55d1..fee4929 100644
--- a/doc/ssm/ssm_nonignorable.qmd
+++ b/doc/ssm/ssm_nonignorable.qmd
@@ -62,7 +62,7 @@ def make_pretty(df, level, n_rep):
 
 ## ATE Coverage
 
-The simulations are based on the  the [make_ssm_data](https://docs.doubleml.org/stable/api/generated/doubleml.datasets.make_ssm_data.html)-DGP with $500$ observations. The simulation considers data with [nonignorable nonresponse](https://docs.doubleml.org/stable/guide/models.html#nonignorable-nonresponse).
+The simulations are based on the [make_ssm_data](https://docs.doubleml.org/stable/api/generated/doubleml.datasets.make_ssm_data.html)-DGP with $500$ observations. The simulation considers data with [nonignorable nonresponse](https://docs.doubleml.org/stable/guide/models.html#nonignorable-nonresponse).
 
 ::: {.callout-note title="Metadata"  collapse="true"}
 

From 006498778b609b07145a7332be3fc32d7ba34e78 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 13:14:35 +0000
Subject: [PATCH 38/58] Update results from script:
 scripts/irm/irm_ate_coverage.py

---
 results/irm/irm_ate_coverage.csv          | 16 ++++++++--------
 results/irm/irm_ate_coverage_metadata.csv |  2 +-
 2 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/results/irm/irm_ate_coverage.csv b/results/irm/irm_ate_coverage.csv
index ea24817..0de042e 100644
--- a/results/irm/irm_ate_coverage.csv
+++ b/results/irm/irm_ate_coverage.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-Lasso,Logistic Regression,0.9,0.875,0.467771360497192,0.12336884150536209,1000
-Lasso,Logistic Regression,0.95,0.935,0.5573839547492131,0.12336884150536209,1000
-Lasso,Random Forest,0.9,0.927,0.6001366139904836,0.14798855067476355,1000
-Lasso,Random Forest,0.95,0.96,0.7151068824313491,0.14798855067476355,1000
-Random Forest,Logistic Regression,0.9,0.796,0.5178418585688922,0.15004402486229945,1000
-Random Forest,Logistic Regression,0.95,0.878,0.6170466331179857,0.15004402486229945,1000
-Random Forest,Random Forest,0.9,0.897,0.6233089219687683,0.150114084240768,1000
-Random Forest,Random Forest,0.95,0.953,0.7427183904293482,0.150114084240768,1000
+Lasso,Logistic Regression,0.9,0.875,0.467771360497192,0.12336884150536219,1000
+Lasso,Logistic Regression,0.95,0.935,0.5573839547492132,0.12336884150536219,1000
+Lasso,Random Forest,0.9,0.906,0.6047145364621751,0.1478860899164366,1000
+Lasso,Random Forest,0.95,0.959,0.7205618135094181,0.1478860899164366,1000
+Random Forest,Logistic Regression,0.9,0.803,0.5176227656141883,0.15019297474976653,1000
+Random Forest,Logistic Regression,0.95,0.883,0.6167855677602845,0.15019297474976653,1000
+Random Forest,Random Forest,0.9,0.899,0.6330777189487165,0.15360554047241584,1000
+Random Forest,Random Forest,0.95,0.959,0.7543586299857805,0.15360554047241584,1000
diff --git a/results/irm/irm_ate_coverage_metadata.csv b/results/irm/irm_ate_coverage_metadata.csv
index cd30335..a6fbf57 100644
--- a/results/irm/irm_ate_coverage_metadata.csv
+++ b/results/irm/irm_ate_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,irm_ate_coverage.py,2024-09-09 08:23:16,3577.3718523979187,3.12.5
+0.10.dev0,irm_ate_coverage.py,2025-01-08 13:14:33,3543.555382013321,3.12.8

From 880e125e79c59f353fb3f60f55a90ba5f6180446 Mon Sep 17 00:00:00 2001
From: SvenKlaassen <sven.klaassen@uni-hamburg.de>
Date: Wed, 8 Jan 2025 14:22:28 +0100
Subject: [PATCH 39/58] add description for rdd simulation

---
 doc/rdd/rdd.qmd | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/doc/rdd/rdd.qmd b/doc/rdd/rdd.qmd
index fff8359..71cd93c 100644
--- a/doc/rdd/rdd.qmd
+++ b/doc/rdd/rdd.qmd
@@ -63,6 +63,8 @@ def make_pretty(df, level, n_rep):
 
 ## Sharp Design
 
+The simulations are based on the [make_simple_rdd_data](https://docs.doubleml.org/stable/api/generated/doubleml.rdd.datasets.make_simple_rdd_data.html#doubleml.rdd.datasets.make_simple_rdd_data)-DGP with $1000$ observations. The simulation considers data under a [sharp regression discontinuity design](https://docs.doubleml.org/stable/guide/models.html#sharp-regression-discontinuity-design).
+
 ::: {.callout-note title="Metadata"  collapse="true"}
 
 ```{python}
@@ -105,6 +107,8 @@ make_pretty(df_ate_9, level, n_rep)
 
 ## Fuzzy Design
 
+The simulations are based on the [make_simple_rdd_data](https://docs.doubleml.org/stable/api/generated/doubleml.rdd.datasets.make_simple_rdd_data.html#doubleml.rdd.datasets.make_simple_rdd_data)-DGP with $2000$ observations. The simulation considers data under a [fuzzy regression discontinuity design](https://docs.doubleml.org/stable/guide/models.html#fuzzy-regression-discontinuity-design).
+
 ::: {.callout-note title="Metadata"  collapse="true"}
 
 ```{python}

From 4b783764e4e872a430f63785370329415e88dd88 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 13:50:48 +0000
Subject: [PATCH 40/58] Update results from script:
 scripts/irm/iivm_late_coverage.py

---
 results/irm/iivm_late_coverage.csv          | 16 ++++++++--------
 results/irm/iivm_late_coverage_metadata.csv |  2 +-
 2 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/results/irm/iivm_late_coverage.csv b/results/irm/iivm_late_coverage.csv
index 9322f98..a8cd4a5 100644
--- a/results/irm/iivm_late_coverage.csv
+++ b/results/irm/iivm_late_coverage.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-Lasso,Logistic Regression,0.9,0.902,0.9293147641314786,0.22417217252344523,1000
-Lasso,Logistic Regression,0.95,0.956,1.1073468411744398,0.22417217252344523,1000
-Lasso,Random Forest,0.9,0.907,0.9551548569821924,0.23030571774269312,1000
-Lasso,Random Forest,0.95,0.965,1.1381372109159926,0.23030571774269312,1000
-Random Forest,Logistic Regression,0.9,0.901,0.9627435648761393,0.2326439704061282,1000
-Random Forest,Logistic Regression,0.95,0.949,1.1471797141014568,0.2326439704061282,1000
-Random Forest,Random Forest,0.9,0.906,0.9916155285633201,0.23508228830266614,1000
-Random Forest,Random Forest,0.95,0.96,1.1815827807711041,0.23508228830266614,1000
+Lasso,Logistic Regression,0.9,0.902,0.9293147641314788,0.2241721725234453,1000
+Lasso,Logistic Regression,0.95,0.956,1.10734684117444,0.2241721725234453,1000
+Lasso,Random Forest,0.9,0.906,0.9553298843030593,0.23080551899825463,1000
+Lasso,Random Forest,0.95,0.96,1.1383457688323866,0.23080551899825463,1000
+Random Forest,Logistic Regression,0.9,0.905,0.9631937131993897,0.23250791933354573,1000
+Random Forest,Logistic Regression,0.95,0.949,1.1477160989121267,0.23250791933354573,1000
+Random Forest,Random Forest,0.9,0.905,0.991691362981023,0.23403696617336237,1000
+Random Forest,Random Forest,0.95,0.962,1.181673143053225,0.23403696617336237,1000
diff --git a/results/irm/iivm_late_coverage_metadata.csv b/results/irm/iivm_late_coverage_metadata.csv
index 12b58dc..b18008f 100644
--- a/results/irm/iivm_late_coverage_metadata.csv
+++ b/results/irm/iivm_late_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,iivm_late_coverage.py,2024-09-09 09:00:39,5819.892728328705,3.12.5
+0.10.dev0,iivm_late_coverage.py,2025-01-08 13:50:46,5734.383908510208,3.12.8

From 19806a52f27f83b519d3a8cdf7883adacac7fb7a Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 14:10:29 +0000
Subject: [PATCH 41/58] Update results from script:
 scripts/plm/plr_ate_coverage.py

---
 results/plm/plr_ate_coverage.csv          | 24 +++++++++++------------
 results/plm/plr_ate_coverage_metadata.csv |  2 +-
 2 files changed, 13 insertions(+), 13 deletions(-)

diff --git a/results/plm/plr_ate_coverage.csv b/results/plm/plr_ate_coverage.csv
index e8eeabf..e1067cc 100644
--- a/results/plm/plr_ate_coverage.csv
+++ b/results/plm/plr_ate_coverage.csv
@@ -3,15 +3,15 @@ Lasso,Lasso,IV-type,0.9,0.881,0.1393979255576113,0.0352891099128789,1000
 Lasso,Lasso,IV-type,0.95,0.945,0.16610287331091153,0.0352891099128789,1000
 Lasso,Lasso,partialling out,0.9,0.908,0.14646362984437974,0.034686755904342816,1000
 Lasso,Lasso,partialling out,0.95,0.956,0.17452217926042807,0.034686755904342816,1000
-Lasso,Random Forest,IV-type,0.9,0.896,0.1466718471783942,0.036271482678477664,1000
-Lasso,Random Forest,IV-type,0.95,0.957,0.17477028551677726,0.036271482678477664,1000
-Lasso,Random Forest,partialling out,0.9,0.817,0.14330947689141327,0.04198736921369438,1000
-Lasso,Random Forest,partialling out,0.95,0.89,0.1707637742034367,0.04198736921369438,1000
-Random Forest,Lasso,IV-type,0.9,0.879,0.14196116082587776,0.03587641777731212,1000
-Random Forest,Lasso,IV-type,0.95,0.946,0.16915715651726354,0.03587641777731212,1000
-Random Forest,Lasso,partialling out,0.9,0.906,0.15199168401588034,0.03621498971623914,1000
-Random Forest,Lasso,partialling out,0.95,0.946,0.18110926208846576,0.03621498971623914,1000
-Random Forest,Random Forest,IV-type,0.9,0.895,0.1494001704377928,0.036878543282509786,1000
-Random Forest,Random Forest,IV-type,0.95,0.953,0.17802128319765598,0.036878543282509786,1000
-Random Forest,Random Forest,partialling out,0.9,0.88,0.14628833002013608,0.03720066374571608,1000
-Random Forest,Random Forest,partialling out,0.95,0.941,0.17431329663623335,0.03720066374571608,1000
+Lasso,Random Forest,IV-type,0.9,0.895,0.14672332096879584,0.03621404411832195,1000
+Lasso,Random Forest,IV-type,0.95,0.953,0.17483162032109167,0.03621404411832195,1000
+Lasso,Random Forest,partialling out,0.9,0.816,0.14332193251141256,0.04209132271298422,1000
+Lasso,Random Forest,partialling out,0.95,0.888,0.17077861599008798,0.04209132271298422,1000
+Random Forest,Lasso,IV-type,0.9,0.883,0.14193144590758777,0.03591650651278451,1000
+Random Forest,Lasso,IV-type,0.95,0.951,0.16912174900823193,0.03591650651278451,1000
+Random Forest,Lasso,partialling out,0.9,0.901,0.1519648979095884,0.03615745065828101,1000
+Random Forest,Lasso,partialling out,0.95,0.952,0.181077344474182,0.03615745065828101,1000
+Random Forest,Random Forest,IV-type,0.9,0.893,0.14942288181113228,0.03672076481604481,1000
+Random Forest,Random Forest,IV-type,0.95,0.948,0.17804834546815554,0.03672076481604481,1000
+Random Forest,Random Forest,partialling out,0.9,0.878,0.14635785065361873,0.037417599679567926,1000
+Random Forest,Random Forest,partialling out,0.95,0.946,0.17439613558042621,0.037417599679567926,1000
diff --git a/results/plm/plr_ate_coverage_metadata.csv b/results/plm/plr_ate_coverage_metadata.csv
index 0ba67da..8d5c7fd 100644
--- a/results/plm/plr_ate_coverage_metadata.csv
+++ b/results/plm/plr_ate_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,plr_ate_coverage.py,2024-09-09 09:19:46,6970.300842285156,3.12.5
+0.10.dev0,plr_ate_coverage.py,2025-01-08 14:10:27,6916.502653360367,3.12.8

From d3347d20db7cbf8e3d081bb446a382b72372653a Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 14:14:02 +0000
Subject: [PATCH 42/58] Update results from script:
 scripts/irm/ssm_mar_ate_coverage.py

---
 results/irm/ssm_mar_ate_coverage.csv          | 24 +++++++++----------
 results/irm/ssm_mar_ate_coverage_metadata.csv |  2 +-
 2 files changed, 13 insertions(+), 13 deletions(-)

diff --git a/results/irm/ssm_mar_ate_coverage.csv b/results/irm/ssm_mar_ate_coverage.csv
index 5a9014d..59a4f8d 100644
--- a/results/irm/ssm_mar_ate_coverage.csv
+++ b/results/irm/ssm_mar_ate_coverage.csv
@@ -1,17 +1,17 @@
 Learner g,Learner m,Learner pi,score,level,Coverage,CI Length,Bias,repetition
 LGBM,LGBM,LGBM,missing-at-random,0.9,0.934,5.894613599209654,1.524603484598883,1000
 LGBM,LGBM,LGBM,missing-at-random,0.95,0.981,7.023865326329001,1.524603484598883,1000
-LGBM,LGBM,Logistic,missing-at-random,0.9,0.927,2.5815888675562886,0.6151192173080173,1000
-LGBM,LGBM,Logistic,missing-at-random,0.95,0.973,3.0761528687981845,0.6151192173080173,1000
-LGBM,Logistic,LGBM,missing-at-random,0.9,0.945,2.5756414334122404,0.6542029876050892,1000
-LGBM,Logistic,LGBM,missing-at-random,0.95,0.985,3.06906606391065,0.6542029876050892,1000
-LGBM,Logistic,Logistic,missing-at-random,0.9,0.914,0.5399737109966924,0.12672360617482684,1000
-LGBM,Logistic,Logistic,missing-at-random,0.95,0.958,0.6434183618596117,0.12672360617482684,1000
+LGBM,LGBM,Logistic,missing-at-random,0.9,0.927,2.581588867556288,0.6151192173080174,1000
+LGBM,LGBM,Logistic,missing-at-random,0.95,0.973,3.0761528687981836,0.6151192173080174,1000
+LGBM,Logistic,LGBM,missing-at-random,0.9,0.945,2.5756414334122413,0.6542029876050892,1000
+LGBM,Logistic,LGBM,missing-at-random,0.95,0.985,3.0690660639106513,0.6542029876050892,1000
+LGBM,Logistic,Logistic,missing-at-random,0.9,0.914,0.5399737109966929,0.12672360617482706,1000
+LGBM,Logistic,Logistic,missing-at-random,0.95,0.958,0.6434183618596122,0.12672360617482706,1000
 Lasso,LGBM,LGBM,missing-at-random,0.9,0.939,5.030966633759897,1.2700343898139361,1000
 Lasso,LGBM,LGBM,missing-at-random,0.95,0.981,5.994766493519136,1.2700343898139361,1000
-Lasso,LGBM,Logistic,missing-at-random,0.9,0.887,2.341425282643257,0.6221402191258445,1000
-Lasso,LGBM,Logistic,missing-at-random,0.95,0.955,2.7899803066231694,0.6221402191258445,1000
-Lasso,Logistic,LGBM,missing-at-random,0.9,0.919,2.2995632695758172,0.6130089902400221,1000
-Lasso,Logistic,LGBM,missing-at-random,0.95,0.97,2.7400986414171333,0.6130089902400221,1000
-Lasso,Logistic,Logistic,missing-at-random,0.9,0.897,0.5116626905293394,0.12267262949094226,1000
-Lasso,Logistic,Logistic,missing-at-random,0.95,0.961,0.609683700262744,0.12267262949094226,1000
+Lasso,LGBM,Logistic,missing-at-random,0.9,0.887,2.3414252826432578,0.6221402191258446,1000
+Lasso,LGBM,Logistic,missing-at-random,0.95,0.955,2.78998030662317,0.6221402191258446,1000
+Lasso,Logistic,LGBM,missing-at-random,0.9,0.919,2.2995632695758177,0.6130089902400226,1000
+Lasso,Logistic,LGBM,missing-at-random,0.95,0.97,2.7400986414171338,0.6130089902400226,1000
+Lasso,Logistic,Logistic,missing-at-random,0.9,0.897,0.5116626905293399,0.12267262949094253,1000
+Lasso,Logistic,Logistic,missing-at-random,0.95,0.961,0.6096837002627445,0.12267262949094253,1000
diff --git a/results/irm/ssm_mar_ate_coverage_metadata.csv b/results/irm/ssm_mar_ate_coverage_metadata.csv
index 8ff1d7a..7a7fba8 100644
--- a/results/irm/ssm_mar_ate_coverage_metadata.csv
+++ b/results/irm/ssm_mar_ate_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,ssm_mar_ate_coverage.py,2024-09-09 09:44:28,8451.34564447403,3.12.5
+0.10.dev0,ssm_mar_ate_coverage.py,2025-01-08 14:14:00,7131.662969589233,3.12.8

From 9ee2846ea79d1b0fc1822dcf1e69d091e9ed95fd Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 14:19:06 +0000
Subject: [PATCH 43/58] Update results from script:
 scripts/irm/irm_cate_coverage.py

---
 results/irm/irm_cate_coverage.csv          | 8 ++++----
 results/irm/irm_cate_coverage_metadata.csv | 2 +-
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/results/irm/irm_cate_coverage.csv b/results/irm/irm_cate_coverage.csv
index 3d56bac..42b5454 100644
--- a/results/irm/irm_cate_coverage.csv
+++ b/results/irm/irm_cate_coverage.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
 LGBM,LGBM,0.9,0.9356475000000001,0.6670555194228769,0.1482947174222056,1.0,1.689294724011131,1000
 LGBM,LGBM,0.95,0.9723379999999999,0.7948456764390678,0.1482947174222056,1.0,1.6897571332817831,1000
-LGBM,Logistic Regression,0.9,0.8889914999999999,0.23544529209287568,0.058506993145254954,0.996,0.595737920698468,1000
-LGBM,Logistic Regression,0.95,0.942037,0.2805503695102737,0.058506993145254954,0.996,0.5990789624833717,1000
+LGBM,Logistic Regression,0.9,0.8889914999999999,0.2354452920928757,0.05850699314525499,0.996,0.5957379206984681,1000
+LGBM,Logistic Regression,0.95,0.942037,0.28055036951027373,0.05850699314525499,0.996,0.5990789624833718,1000
 Lasso,LGBM,0.9,0.896289,0.6428742805642967,0.15829333167540963,1.0,1.6320898187101593,1000
 Lasso,LGBM,0.95,0.9491539999999999,0.7660319531461224,0.15829333167540963,1.0,1.6337799284392311,1000
-Lasso,Logistic Regression,0.9,0.8892920000000001,0.24738399667726235,0.061668240816651954,0.998,0.6298396366786109,1000
-Lasso,Logistic Regression,0.95,0.9413365,0.2947762134541078,0.061668240816651954,0.997,0.6288417962868702,1000
+Lasso,Logistic Regression,0.9,0.8892920000000001,0.2473839966772624,0.061668240816652016,0.998,0.629839636678611,1000
+Lasso,Logistic Regression,0.95,0.9413365,0.29477621345410787,0.061668240816652016,0.997,0.6288417962868702,1000
diff --git a/results/irm/irm_cate_coverage_metadata.csv b/results/irm/irm_cate_coverage_metadata.csv
index a9b76cb..24d54ab 100644
--- a/results/irm/irm_cate_coverage_metadata.csv
+++ b/results/irm/irm_cate_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,irm_cate_coverage.py,2024-09-09 10:07:30,9833.500946998596,3.12.5
+0.10.dev0,irm_cate_coverage.py,2025-01-08 14:19:05,7429.032528162003,3.12.8

From e8ee5315cf90e4603cedadeee7b74ede57c83dd6 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 14:24:21 +0000
Subject: [PATCH 44/58] Update results from script:
 scripts/irm/ssm_nonignorable_ate_coverage.py

---
 results/irm/ssm_nonignorable_ate_coverage.csv | 24 +++++++++----------
 ...ssm_nonignorable_ate_coverage_metadata.csv |  2 +-
 2 files changed, 13 insertions(+), 13 deletions(-)

diff --git a/results/irm/ssm_nonignorable_ate_coverage.csv b/results/irm/ssm_nonignorable_ate_coverage.csv
index 6d5265a..f85fc53 100644
--- a/results/irm/ssm_nonignorable_ate_coverage.csv
+++ b/results/irm/ssm_nonignorable_ate_coverage.csv
@@ -1,17 +1,17 @@
 Learner g,Learner m,Learner pi,score,level,Coverage,CI Length,Bias,repetition
 LGBM,LGBM,LGBM,nonignorable,0.9,0.919,13.007296321798503,3.6668819438868456,1000
 LGBM,LGBM,LGBM,nonignorable,0.95,0.966,15.499149534791721,3.6668819438868456,1000
-LGBM,LGBM,Logistic,nonignorable,0.9,0.918,4.832148171492925,1.3269099332105847,1000
-LGBM,LGBM,Logistic,nonignorable,0.95,0.974,5.757859683624376,1.3269099332105847,1000
-LGBM,Logistic,LGBM,nonignorable,0.9,0.897,4.592630929679537,1.2319933070953284,1000
-LGBM,Logistic,LGBM,nonignorable,0.95,0.959,5.472457286755379,1.2319933070953284,1000
-LGBM,Logistic,Logistic,nonignorable,0.9,0.867,2.530181172735919,0.7278088971445482,1000
-LGBM,Logistic,Logistic,nonignorable,0.95,0.94,3.0148968222264956,0.7278088971445482,1000
+LGBM,LGBM,Logistic,nonignorable,0.9,0.918,4.832148171492935,1.326909933210586,1000
+LGBM,LGBM,Logistic,nonignorable,0.95,0.974,5.757859683624388,1.326909933210586,1000
+LGBM,Logistic,LGBM,nonignorable,0.9,0.897,4.592630929679517,1.2319933070953264,1000
+LGBM,Logistic,LGBM,nonignorable,0.95,0.959,5.472457286755355,1.2319933070953264,1000
+LGBM,Logistic,Logistic,nonignorable,0.9,0.867,2.5301811727355052,0.7278088971443857,1000
+LGBM,Logistic,Logistic,nonignorable,0.95,0.94,3.014896822226002,0.7278088971443857,1000
 Lasso,LGBM,LGBM,nonignorable,0.9,0.931,10.203902842326483,2.892343371671614,1000
 Lasso,LGBM,LGBM,nonignorable,0.95,0.975,12.158700169432056,2.892343371671614,1000
-Lasso,LGBM,Logistic,nonignorable,0.9,0.917,7.0625497859220685,2.0505032981783837,1000
-Lasso,LGBM,Logistic,nonignorable,0.95,0.974,8.415547129919004,2.0505032981783837,1000
-Lasso,Logistic,LGBM,nonignorable,0.9,0.894,4.170596833405643,1.1867597841647153,1000
-Lasso,Logistic,LGBM,nonignorable,0.95,0.95,4.969572643774837,1.1867597841647153,1000
-Lasso,Logistic,Logistic,nonignorable,0.9,0.87,1.9933166328366938,0.5662899386624944,1000
-Lasso,Logistic,Logistic,nonignorable,0.95,0.928,2.3751832662371193,0.5662899386624944,1000
+Lasso,LGBM,Logistic,nonignorable,0.9,0.917,7.062549785922076,2.0505032981783877,1000
+Lasso,LGBM,Logistic,nonignorable,0.95,0.974,8.415547129919013,2.0505032981783877,1000
+Lasso,Logistic,LGBM,nonignorable,0.9,0.894,4.170596833405628,1.1867597841647148,1000
+Lasso,Logistic,LGBM,nonignorable,0.95,0.95,4.969572643774819,1.1867597841647148,1000
+Lasso,Logistic,Logistic,nonignorable,0.9,0.87,1.9933166328368466,0.5662899386625126,1000
+Lasso,Logistic,Logistic,nonignorable,0.95,0.928,2.375183266237302,0.5662899386625126,1000
diff --git a/results/irm/ssm_nonignorable_ate_coverage_metadata.csv b/results/irm/ssm_nonignorable_ate_coverage_metadata.csv
index c0ae92d..56ee090 100644
--- a/results/irm/ssm_nonignorable_ate_coverage_metadata.csv
+++ b/results/irm/ssm_nonignorable_ate_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,ssm_nonignorable_ate_coverage.py,2024-09-09 08:50:13,5195.712763547897,3.12.5
+0.10.dev0,ssm_nonignorable_ate_coverage.py,2025-01-08 14:24:21,7745.532069444656,3.12.8

From 5b4cc9b4101cd3ccfc355887cb9adcb7ce1649d0 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 14:25:32 +0000
Subject: [PATCH 45/58] Update results from script:
 scripts/plm/plr_cate_coverage.py

---
 results/plm/plr_cate_coverage_metadata.csv | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/results/plm/plr_cate_coverage_metadata.csv b/results/plm/plr_cate_coverage_metadata.csv
index 889fdf3..59b490d 100644
--- a/results/plm/plr_cate_coverage_metadata.csv
+++ b/results/plm/plr_cate_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,plr_cate_coverage.py,2024-09-09 09:52:53,8957.487109184265,3.12.5
+0.10.dev0,plr_cate_coverage.py,2025-01-08 14:25:31,7808.868787527084,3.12.8

From 277cb24131de14c776b7cad35d784191d97359b6 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 14:51:21 +0000
Subject: [PATCH 46/58] Update results from script:
 scripts/irm/irm_ate_sensitivity.py

---
 results/irm/irm_ate_sensitivity.csv          | 8 ++++----
 results/irm/irm_ate_sensitivity_metadata.csv | 2 +-
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/results/irm/irm_ate_sensitivity.csv b/results/irm/irm_ate_sensitivity.csv
index 34ac6c7..6e10770 100644
--- a/results/irm/irm_ate_sensitivity.csv
+++ b/results/irm/irm_ate_sensitivity.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,Coverage (Lower),Coverage (Upper),RV,RVa,Bias (Lower),Bias (Upper),repetition
 LGBM,LGBM,0.9,0.112,0.266748233354866,0.17891290135375168,0.962,1.0,0.12379347892727971,0.05409589192160397,0.04254708028278409,0.32210978560617337,500
 LGBM,LGBM,0.95,0.318,0.31785012462427936,0.17891290135375168,0.998,1.0,0.12379347892727971,0.03441021667548556,0.04254708028278409,0.32210978560617337,500
-LGBM,Logistic Regr.,0.9,0.292,0.2577778025822409,0.14922926552528684,1.0,1.0,0.100665719512958,0.03493291437943745,0.029012990398602393,0.2979424530565633,500
-LGBM,Logistic Regr.,0.95,0.548,0.30716119707955875,0.14922926552528684,1.0,1.0,0.100665719512958,0.018697523014548616,0.029012990398602393,0.2979424530565633,500
+LGBM,Logistic Regr.,0.9,0.292,0.2577778025822409,0.14922926552528684,1.0,1.0,0.10066571951295798,0.03493291437943745,0.029012990398602386,0.2979424530565633,500
+LGBM,Logistic Regr.,0.95,0.548,0.30716119707955875,0.14922926552528684,1.0,1.0,0.10066571951295798,0.01869752301454861,0.029012990398602386,0.2979424530565633,500
 Linear Reg.,LGBM,0.9,0.122,0.2675665174758639,0.17873104426193565,0.964,1.0,0.12647219547900976,0.05512739569620471,0.04513946154555041,0.31857328180879246,500
 Linear Reg.,LGBM,0.95,0.314,0.31882517029399604,0.17873104426193565,0.998,1.0,0.12647219547900976,0.035017588858111126,0.04513946154555041,0.31857328180879246,500
-Linear Reg.,Logistic Regr.,0.9,0.86,0.2592281409673473,0.08970251629543106,1.0,1.0,0.06300567732617765,0.006719868195974335,0.05720312141493261,0.23496869651774063,500
-Linear Reg.,Logistic Regr.,0.95,0.974,0.30888938185760084,0.08970251629543106,1.0,1.0,0.06300567732617765,0.0014945204694376403,0.05720312141493261,0.23496869651774063,500
+Linear Reg.,Logistic Regr.,0.9,0.86,0.2592281409673473,0.08970251629543106,1.0,1.0,0.06300567732617765,0.006719868195974334,0.05720312141493262,0.23496869651774063,500
+Linear Reg.,Logistic Regr.,0.95,0.974,0.30888938185760084,0.08970251629543106,1.0,1.0,0.06300567732617765,0.0014945204694376396,0.05720312141493262,0.23496869651774063,500
diff --git a/results/irm/irm_ate_sensitivity_metadata.csv b/results/irm/irm_ate_sensitivity_metadata.csv
index 744233a..c038f24 100644
--- a/results/irm/irm_ate_sensitivity_metadata.csv
+++ b/results/irm/irm_ate_sensitivity_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,irm_ate_sensitivity.py,2024-09-09 09:57:25,9228.398559331894,3.12.5
+0.10.dev0,irm_ate_sensitivity.py,2025-01-08 14:51:20,9351.407655954361,3.12.8

From 6bb124d6798045dfd367d9c075c9f8901355b187 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 15:02:53 +0000
Subject: [PATCH 47/58] Update results from script:
 scripts/irm/irm_apo_coverage.py

---
 results/irm/irm_apo_coverage_apo.csv          | 48 +++++++++----------
 results/irm/irm_apo_coverage_apos.csv         | 16 +++----
 .../irm/irm_apo_coverage_apos_contrast.csv    | 16 +++----
 results/irm/irm_apo_coverage_metadata.csv     |  2 +-
 4 files changed, 41 insertions(+), 41 deletions(-)

diff --git a/results/irm/irm_apo_coverage_apo.csv b/results/irm/irm_apo_coverage_apo.csv
index ca4b92b..c4e8851 100644
--- a/results/irm/irm_apo_coverage_apo.csv
+++ b/results/irm/irm_apo_coverage_apo.csv
@@ -1,25 +1,25 @@
 Learner g,Learner m,Treatment Level,level,Coverage,CI Length,Bias,repetition
-LGBM,LGBM,0.0,0.9,0.912,8.657690136121921,2.0760855366229958,1000
-LGBM,LGBM,0.0,0.95,0.965,10.316274091547035,2.0760855366229958,1000
-LGBM,LGBM,1.0,0.9,0.915,38.23339285821166,9.180525200256618,1000
-LGBM,LGBM,1.0,0.95,0.967,45.55789754237906,9.180525200256618,1000
-LGBM,LGBM,2.0,0.9,0.89,37.49194764946096,9.610674399165429,1000
-LGBM,LGBM,2.0,0.95,0.952,44.67441108385784,9.610674399165429,1000
-LGBM,Logistic,0.0,0.9,0.904,5.625897101886533,1.3345731610342202,1000
-LGBM,Logistic,0.0,0.95,0.955,6.7036698705295725,1.3345731610342202,1000
-LGBM,Logistic,1.0,0.9,0.924,7.423300143143786,1.697057819214677,1000
-LGBM,Logistic,1.0,0.95,0.968,8.84540769378873,1.697057819214677,1000
-LGBM,Logistic,2.0,0.9,0.917,7.321275660150267,1.660826093332619,1000
-LGBM,Logistic,2.0,0.95,0.971,8.723838024042964,1.660826093332619,1000
-Linear,LGBM,0.0,0.9,0.901,5.498257423071024,1.30423568882223,1000
-Linear,LGBM,0.0,0.95,0.95,6.551577812380716,1.30423568882223,1000
-Linear,LGBM,1.0,0.9,0.949,10.700720020780512,2.1264975614784354,1000
-Linear,LGBM,1.0,0.95,0.982,12.75069435099058,2.1264975614784354,1000
-Linear,LGBM,2.0,0.9,0.93,7.513644049429104,1.6338972741785736,1000
-Linear,LGBM,2.0,0.95,0.965,8.953059097926168,1.6338972741785736,1000
-Linear,Logistic,0.0,0.9,0.902,5.335670092717667,1.2832290098794459,1000
-Linear,Logistic,0.0,0.95,0.954,6.357843058957276,1.2832290098794459,1000
-Linear,Logistic,1.0,0.9,0.905,5.417512107920403,1.2812664745065607,1000
-Linear,Logistic,1.0,0.95,0.956,6.455363835025866,1.2812664745065607,1000
-Linear,Logistic,2.0,0.9,0.908,5.366403391397197,1.2775297528572058,1000
-Linear,Logistic,2.0,0.95,0.958,6.3944640430685675,1.2775297528572058,1000
+LGBM,LGBM,0.0,0.9,0.911,8.657690136121921,2.0760918678352267,1000
+LGBM,LGBM,0.0,0.95,0.963,10.316274091547035,2.0760918678352267,1000
+LGBM,LGBM,1.0,0.9,0.914,38.23339285821166,9.19332007236871,1000
+LGBM,LGBM,1.0,0.95,0.967,45.55789754237906,9.19332007236871,1000
+LGBM,LGBM,2.0,0.9,0.891,37.49194764946096,9.594147407062762,1000
+LGBM,LGBM,2.0,0.95,0.952,44.67441108385784,9.594147407062762,1000
+LGBM,Logistic,0.0,0.9,0.901,5.625897101886533,1.3366474407456235,1000
+LGBM,Logistic,0.0,0.95,0.955,6.7036698705295725,1.3366474407456235,1000
+LGBM,Logistic,1.0,0.9,0.92,7.423300143143785,1.6954254817667072,1000
+LGBM,Logistic,1.0,0.95,0.968,8.84540769378873,1.6954254817667072,1000
+LGBM,Logistic,2.0,0.9,0.918,7.321275660150268,1.660607504960853,1000
+LGBM,Logistic,2.0,0.95,0.971,8.723838024042964,1.660607504960853,1000
+Linear,LGBM,0.0,0.9,0.901,5.498257423071024,1.307400569952483,1000
+Linear,LGBM,0.0,0.95,0.949,6.551577812380716,1.307400569952483,1000
+Linear,LGBM,1.0,0.9,0.951,10.700720020780512,2.1270559074131152,1000
+Linear,LGBM,1.0,0.95,0.982,12.75069435099058,2.1270559074131152,1000
+Linear,LGBM,2.0,0.9,0.932,7.513644049429104,1.634643965398859,1000
+Linear,LGBM,2.0,0.95,0.967,8.953059097926168,1.634643965398859,1000
+Linear,Logistic,0.0,0.9,0.9,5.335670092717667,1.2859337252007816,1000
+Linear,Logistic,0.0,0.95,0.951,6.357843058957276,1.2859337252007816,1000
+Linear,Logistic,1.0,0.9,0.904,5.417512107920403,1.2802845007629777,1000
+Linear,Logistic,1.0,0.95,0.954,6.455363835025866,1.2802845007629777,1000
+Linear,Logistic,2.0,0.9,0.905,5.366403391397197,1.2808554104576877,1000
+Linear,Logistic,2.0,0.95,0.959,6.3944640430685675,1.2808554104576877,1000
diff --git a/results/irm/irm_apo_coverage_apos.csv b/results/irm/irm_apo_coverage_apos.csv
index 48a0fba..9450b8b 100644
--- a/results/irm/irm_apo_coverage_apos.csv
+++ b/results/irm/irm_apo_coverage_apos.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
-LGBM,LGBM,0.9,0.906,28.21021843292038,7.120657478889542,0.924,36.1943517986729,1000
-LGBM,LGBM,0.95,0.9586666666666667,33.61454856442563,7.120657478889542,0.974,40.868020474452145,1000
-LGBM,Logistic,0.9,0.918,6.789316986971467,1.5705977914191496,0.925,8.394070597867524,1000
-LGBM,Logistic,0.95,0.962,8.089970168806186,1.5705977914191496,0.961,9.592284619044477,1000
-Linear,LGBM,0.9,0.9276666666666666,7.903418354805325,1.7245563336966274,0.94,9.850445774370156,1000
-Linear,LGBM,0.95,0.9666666666666667,9.41750382912841,1.7245563336966274,0.975,11.234392064837424,1000
-Linear,Logistic,0.9,0.903,5.372532806955153,1.278875142245648,0.906,5.7964894175017925,1000
-Linear,Logistic,0.95,0.9556666666666667,6.4017676921854445,1.278875142245648,0.953,6.8182385960659,1000
+LGBM,LGBM,0.9,0.9063333333333333,28.21021843292038,7.1182934844676025,0.925,36.1943517986729,1000
+LGBM,LGBM,0.95,0.9583333333333334,33.61454856442563,7.1182934844676025,0.973,40.868020474452145,1000
+LGBM,Logistic,0.9,0.9153333333333333,6.789316986971467,1.5714825799469632,0.924,8.394070597867524,1000
+LGBM,Logistic,0.95,0.963,8.089970168806186,1.5714825799469632,0.959,9.592284619044477,1000
+Linear,LGBM,0.9,0.9266666666666666,7.903418354805325,1.726298806364679,0.939,9.850445774370156,1000
+Linear,LGBM,0.95,0.967,9.41750382912841,1.726298806364679,0.974,11.234392064837424,1000
+Linear,Logistic,0.9,0.904,5.372532806955153,1.2803595601237736,0.906,5.7964894175017925,1000
+Linear,Logistic,0.95,0.957,6.4017676921854445,1.2803595601237736,0.953,6.8182385960659,1000
diff --git a/results/irm/irm_apo_coverage_apos_contrast.csv b/results/irm/irm_apo_coverage_apos_contrast.csv
index 36dea44..c663a0b 100644
--- a/results/irm/irm_apo_coverage_apos_contrast.csv
+++ b/results/irm/irm_apo_coverage_apos_contrast.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
-LGBM,LGBM,0.9,0.8885,37.87536523730769,9.788503277093351,0.898,44.828925781533165,1000
-LGBM,LGBM,0.95,0.9485,45.13128131893863,9.788503277093351,0.965,51.42387403222799,1000
-LGBM,Logistic,0.9,0.9275,5.725128733165455,1.267381146072165,0.927,6.774304315459576,1000
-LGBM,Logistic,0.95,0.963,6.821911652197591,1.267381146072165,0.962,7.7654094416927215,1000
-Linear,LGBM,0.9,0.958,7.430953406859927,1.5064356327113417,0.975,8.798628447594016,1000
-Linear,LGBM,0.95,0.989,8.85452711998085,1.5064356327113417,0.992,10.090116294778499,1000
-Linear,Logistic,0.9,0.872,1.1425883251377777,0.29482653859949187,0.871,1.3505222299078565,1000
-Linear,Logistic,0.95,0.936,1.3614779635902856,0.29482653859949187,0.92,1.5496710496635275,1000
+LGBM,LGBM,0.9,0.8885,37.87536523730769,9.786356896553793,0.898,44.828925781533165,1000
+LGBM,LGBM,0.95,0.9485,45.13128131893863,9.786356896553793,0.965,51.42387403222799,1000
+LGBM,Logistic,0.9,0.9275,5.725128733165455,1.2679354841429349,0.926,6.774304315459575,1000
+LGBM,Logistic,0.95,0.962,6.821911652197591,1.2679354841429349,0.961,7.7654094416927215,1000
+Linear,LGBM,0.9,0.958,7.430953406859927,1.5066894086042675,0.975,8.798628447594016,1000
+Linear,LGBM,0.95,0.9885,8.85452711998085,1.5066894086042675,0.992,10.090116294778499,1000
+Linear,Logistic,0.9,0.873,1.1425883251377777,0.29743753232068365,0.869,1.3505222299078565,1000
+Linear,Logistic,0.95,0.9335,1.3614779635902856,0.29743753232068365,0.916,1.5496710496635275,1000
diff --git a/results/irm/irm_apo_coverage_metadata.csv b/results/irm/irm_apo_coverage_metadata.csv
index d2aff99..5fac53a 100644
--- a/results/irm/irm_apo_coverage_metadata.csv
+++ b/results/irm/irm_apo_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,irm_apo_coverage.py,2024-09-09 10:19:31,10550.167822599411,3.12.5
+0.10.dev0,irm_apo_coverage.py,2025-01-08 15:02:49,10054.695460557938,3.12.8

From 625b89fc5743554d5a8f78f24c2d3561cc89f239 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 15:14:53 +0000
Subject: [PATCH 48/58] Update results from script:
 scripts/irm/irm_atte_sensitivity.py

---
 results/irm/irm_atte_sensitivity.csv          | 8 ++++----
 results/irm/irm_atte_sensitivity_metadata.csv | 2 +-
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/results/irm/irm_atte_sensitivity.csv b/results/irm/irm_atte_sensitivity.csv
index cd6a85e..7483e17 100644
--- a/results/irm/irm_atte_sensitivity.csv
+++ b/results/irm/irm_atte_sensitivity.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,Coverage (Lower),Coverage (Upper),RV,RVa,Bias (Lower),Bias (Upper),repetition
 LGBM,LGBM,0.9,0.702,0.348892741328716,0.13535473129404849,0.95,1.0,0.10509293446782587,0.024288450266824614,0.0649958270073569,0.25876253126104387,500
 LGBM,LGBM,0.95,0.826,0.41573134306126747,0.13535473129404849,0.982,1.0,0.10509293446782587,0.012452066983782133,0.0649958270073569,0.25876253126104387,500
-LGBM,Logistic Regr.,0.9,0.714,0.34666910502599596,0.13078975736827733,0.964,1.0,0.09817018528214369,0.02224699823797256,0.0654544233024662,0.2589976808508975,500
-LGBM,Logistic Regr.,0.95,0.834,0.41308171698108886,0.13078975736827733,0.984,1.0,0.09817018528214369,0.010949342084431749,0.0654544233024662,0.2589976808508975,500
+LGBM,Logistic Regr.,0.9,0.714,0.34666910502599596,0.13078975736827733,0.964,1.0,0.09817018528214369,0.022246998237972562,0.06545442330246619,0.2589976808508975,500
+LGBM,Logistic Regr.,0.95,0.834,0.41308171698108886,0.13078975736827733,0.984,1.0,0.09817018528214369,0.010949342084431752,0.06545442330246619,0.2589976808508975,500
 Linear Reg.,LGBM,0.9,0.754,0.3496967006881292,0.12455057551341779,0.962,1.0,0.09867724125956986,0.02021759355041513,0.06504946816195573,0.24393419014571052,500
 Linear Reg.,LGBM,0.95,0.858,0.416689319724762,0.12455057551341779,0.986,1.0,0.09867724125956986,0.009856683129418061,0.06504946816195573,0.24393419014571052,500
-Linear Reg.,Logistic Regr.,0.9,0.948,0.3502540540945954,0.07444772768321124,0.996,1.0,0.0584014583662732,0.004181143741279687,0.09544484272838329,0.17545346180009289,500
-Linear Reg.,Logistic Regr.,0.95,0.976,0.41735344727108903,0.07444772768321124,0.998,1.0,0.0584014583662732,0.001573924919578164,0.09544484272838329,0.17545346180009289,500
+Linear Reg.,Logistic Regr.,0.9,0.948,0.3502540540945954,0.07444772768321124,0.996,1.0,0.05840145836627319,0.0041811437412796835,0.09544484272838329,0.17545346180009289,500
+Linear Reg.,Logistic Regr.,0.95,0.976,0.41735344727108903,0.07444772768321124,0.998,1.0,0.05840145836627319,0.001573924919578166,0.09544484272838329,0.17545346180009289,500
diff --git a/results/irm/irm_atte_sensitivity_metadata.csv b/results/irm/irm_atte_sensitivity_metadata.csv
index 09e20a9..4353523 100644
--- a/results/irm/irm_atte_sensitivity_metadata.csv
+++ b/results/irm/irm_atte_sensitivity_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,irm_atte_sensitivity.py,2024-09-09 10:03:27,9588.962257862091,3.12.5
+0.10.dev0,irm_atte_sensitivity.py,2025-01-08 15:14:53,10782.067339658737,3.12.8

From f196f2d133af2c0c57235446fb705cd79587b15d Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 16:22:30 +0000
Subject: [PATCH 49/58] Update results from script:
 scripts/did/did_pa_atte_coverage.py

---
 results/did/did_pa_atte_coverage_metadata.csv | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/results/did/did_pa_atte_coverage_metadata.csv b/results/did/did_pa_atte_coverage_metadata.csv
index b35d01b..65f1786 100644
--- a/results/did/did_pa_atte_coverage_metadata.csv
+++ b/results/did/did_pa_atte_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,did_pa_atte_coverage.py,2024-09-09 11:44:15,15625.949723243713,3.12.5
+0.10.dev0,did_pa_atte_coverage.py,2025-01-08 16:22:26,14811.1988697052,3.12.8

From 9622ba4a3076a191fb2e9e30bd2d3cb4e9e15969 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 16:36:14 +0000
Subject: [PATCH 50/58] Update results from script:
 scripts/plm/plr_ate_sensitivity.py

---
 results/plm/plr_ate_sensitivity.csv          | 24 ++++++++++----------
 results/plm/plr_ate_sensitivity_metadata.csv |  2 +-
 2 files changed, 13 insertions(+), 13 deletions(-)

diff --git a/results/plm/plr_ate_sensitivity.csv b/results/plm/plr_ate_sensitivity.csv
index dc0f40d..00934b4 100644
--- a/results/plm/plr_ate_sensitivity.csv
+++ b/results/plm/plr_ate_sensitivity.csv
@@ -3,15 +3,15 @@ LGBM,LGBM,IV-type,0.9,0.49,1.2836841849471865,0.642852034975727,1.0,0.998,0.0883
 LGBM,LGBM,IV-type,0.95,0.65,1.529604050351386,0.642852034975727,1.0,1.0,0.0883267598773138,0.013790413915027113,1.3451446703513257,0.27137365708627864,500
 LGBM,LGBM,partialling out,0.9,0.052,1.0555526522517718,0.9216896766797483,1.0,0.878,0.12290629723561408,0.0667859903596657,1.6463724503661545,0.2830593598175856,500
 LGBM,LGBM,partialling out,0.95,0.114,1.2577685626857555,0.9216896766797483,1.0,0.962,0.12290629723561408,0.05210975377693211,1.6463724503661545,0.2830593598175856,500
-LGBM,Random Forest,IV-type,0.9,0.078,1.184374175040171,0.9303727898138584,1.0,0.93,0.11734531842973916,0.058352142660030235,1.69604622782609,0.2643812093502701,500
-LGBM,Random Forest,IV-type,0.95,0.156,1.4112688747875797,0.9303727898138584,1.0,0.99,0.11734531842973916,0.04323181121508746,1.69604622782609,0.2643812093502701,500
-LGBM,Random Forest,partialling out,0.9,0.084,1.2435979692296912,0.9936323407573932,1.0,0.922,0.11823008469813917,0.059953740141804185,1.808730525763834,0.28983882276077305,500
-LGBM,Random Forest,partialling out,0.95,0.15,1.4818383781995061,0.9936323407573932,1.0,0.98,0.11823008469813917,0.044968170232848895,1.808730525763834,0.28983882276077305,500
-Random Forest,LGBM,IV-type,0.9,0.578,1.901432984855821,0.8851340786844124,1.0,0.998,0.07172805783693792,0.017973636776769754,2.1182623031362136,0.46763713903364934,500
-Random Forest,LGBM,IV-type,0.95,0.76,2.2656971467065694,0.8851340786844124,1.0,1.0,0.07172805783693792,0.00845453203170999,2.1182623031362136,0.46763713903364934,500
-Random Forest,LGBM,partialling out,0.9,0.0,1.5151603860403846,1.5745474280897056,1.0,0.822,0.12823732317433292,0.08050869779411943,2.776861477164536,0.4034510284688934,500
-Random Forest,LGBM,partialling out,0.95,0.004,1.8054249562283828,1.5745474280897056,1.0,0.95,0.12823732317433292,0.06699482596842689,2.776861477164536,0.4034510284688934,500
-Random Forest,Random Forest,IV-type,0.9,0.012,1.7145713653083217,1.6172976560808119,1.0,0.892,0.11945164498301562,0.07039474321397683,2.9458275814460917,0.4036703674065015,500
-Random Forest,Random Forest,IV-type,0.95,0.046,2.0430377936766546,1.6172976560808119,1.0,0.976,0.11945164498301562,0.05654861229503384,2.9458275814460917,0.4036703674065015,500
-Random Forest,Random Forest,partialling out,0.9,0.0,1.738078162618324,1.7342386320328749,1.0,0.818,0.1279559082185197,0.07815181936018857,3.058821980497253,0.4608008360779255,500
-Random Forest,Random Forest,partialling out,0.95,0.022,2.071047870296588,1.7342386320328749,1.0,0.944,0.1279559082185197,0.06407192337097008,3.058821980497253,0.4608008360779255,500
+LGBM,Random Forest,IV-type,0.9,0.072,1.1846157067784349,0.9322070273917288,1.0,0.934,0.11754241223304673,0.058515658188839345,1.6980814469560257,0.26726499739118403,500
+LGBM,Random Forest,IV-type,0.95,0.16,1.4115566776050241,0.9322070273917288,1.0,0.994,0.11754241223304673,0.04334326180178758,1.6980814469560257,0.26726499739118403,500
+LGBM,Random Forest,partialling out,0.9,0.078,1.2415314353647366,0.9950962660593035,1.0,0.918,0.11842149116467734,0.06021024644530299,1.8099982510012884,0.29229694861359934,500
+LGBM,Random Forest,partialling out,0.95,0.15,1.479375951220122,0.9950962660593035,1.0,0.98,0.11842149116467734,0.04525082945770369,1.8099982510012884,0.29229694861359934,500
+Random Forest,LGBM,IV-type,0.9,0.554,1.900486623597139,0.8881666888956794,1.0,1.0,0.07201385567825232,0.01814220891090863,2.11967639571274,0.46266796209857214,500
+Random Forest,LGBM,IV-type,0.95,0.746,2.2645694877143114,0.8881666888956794,1.0,1.0,0.07201385567825232,0.008578785415219068,2.11967639571274,0.46266796209857214,500
+Random Forest,LGBM,partialling out,0.9,0.002,1.5126486531347854,1.573242725840773,1.0,0.818,0.12824967172299567,0.08055028818351519,2.774465314925881,0.4031005519125824,500
+Random Forest,LGBM,partialling out,0.95,0.008,1.8024320418722997,1.573242725840773,1.0,0.948,0.12824967172299567,0.06705003584560411,2.774465314925881,0.4031005519125824,500
+Random Forest,Random Forest,IV-type,0.9,0.012,1.7129890288584426,1.6194855098925158,1.0,0.892,0.11959162432568951,0.07060214596391444,2.948463222220921,0.39969580126755805,500
+Random Forest,Random Forest,IV-type,0.95,0.038,2.041152323503278,1.6194855098925158,1.0,0.972,0.11959162432568951,0.05677408319758889,2.948463222220921,0.39969580126755805,500
+Random Forest,Random Forest,partialling out,0.9,0.0,1.7381117353695532,1.7366675645551972,1.0,0.824,0.1281371703134689,0.07833372270549209,3.0610973455175285,0.4635968018257515,500
+Random Forest,Random Forest,partialling out,0.95,0.018,2.0710878746970973,1.7366675645551972,1.0,0.946,0.1281371703134689,0.0642547167440049,3.0610973455175285,0.4635968018257515,500
diff --git a/results/plm/plr_ate_sensitivity_metadata.csv b/results/plm/plr_ate_sensitivity_metadata.csv
index 72d67cb..f0d1e74 100644
--- a/results/plm/plr_ate_sensitivity_metadata.csv
+++ b/results/plm/plr_ate_sensitivity_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,plr_ate_sensitivity.py,2024-09-09 11:52:27,16128.665112733841,3.12.5
+0.10.dev0,plr_ate_sensitivity.py,2025-01-08 16:36:12,15659.224347829819,3.12.8

From 015ec2dfe0a5240dde926a82a465b496db85de6f Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 16:49:01 +0000
Subject: [PATCH 51/58] Update results from script:
 scripts/irm/cvar_coverage.py

---
 results/irm/cvar_coverage_metadata.csv |  2 +-
 results/irm/cvar_coverage_pq0.csv      | 16 ++++++++--------
 results/irm/cvar_coverage_pq1.csv      | 16 ++++++++--------
 results/irm/cvar_coverage_qte.csv      | 16 ++++++++--------
 4 files changed, 25 insertions(+), 25 deletions(-)

diff --git a/results/irm/cvar_coverage_metadata.csv b/results/irm/cvar_coverage_metadata.csv
index a19cb5b..6b80d0c 100644
--- a/results/irm/cvar_coverage_metadata.csv
+++ b/results/irm/cvar_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,cvar_coverage.py,2024-09-09 11:59:26,16546.96124267578,3.12.5
+0.10.dev0,cvar_coverage.py,2025-01-08 16:49:01,16412.1168384552,3.12.8
diff --git a/results/irm/cvar_coverage_pq0.csv b/results/irm/cvar_coverage_pq0.csv
index e3a4fa3..a9650d4 100644
--- a/results/irm/cvar_coverage_pq0.csv
+++ b/results/irm/cvar_coverage_pq0.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-LGBM,LGBM,0.9,0.8876923076923078,0.5699689541680535,0.13934148600639645,100
-LGBM,LGBM,0.95,0.9461538461538461,0.6791598985897508,0.13934148600639645,100
-LGBM,Logistic Regression,0.9,0.8192307692307692,0.4060118886357097,0.1185635852924032,100
-LGBM,Logistic Regression,0.95,0.89,0.48379300503226824,0.1185635852924032,100
-Linear,LGBM,0.9,0.77,0.5801661718639771,0.17503081399943532,100
-Linear,LGBM,0.95,0.8607692307692308,0.691310632915921,0.17503081399943532,100
-Linear,Logistic Regression,0.9,0.6892307692307692,0.4294636844188598,0.15444826651283644,100
-Linear,Logistic Regression,0.95,0.7776923076923077,0.5117375432906374,0.15444826651283644,100
+LGBM,LGBM,0.9,0.8884615384615384,0.5699689541680535,0.13934954721406115,100
+LGBM,LGBM,0.95,0.9461538461538461,0.6791598985897508,0.13934954721406115,100
+LGBM,Logistic Regression,0.9,0.8192307692307692,0.4060217020758364,0.11848308187809455,100
+LGBM,Logistic Regression,0.95,0.8892307692307692,0.48380469846741503,0.11848308187809455,100
+Linear,LGBM,0.9,0.7692307692307692,0.5801661718639771,0.1751137266106609,100
+Linear,LGBM,0.95,0.8615384615384616,0.691310632915921,0.1751137266106609,100
+Linear,Logistic Regression,0.9,0.6892307692307692,0.42946981193983413,0.1545041280672664,100
+Linear,Logistic Regression,0.95,0.7776923076923077,0.5117448446822186,0.1545041280672664,100
diff --git a/results/irm/cvar_coverage_pq1.csv b/results/irm/cvar_coverage_pq1.csv
index 167f61d..a364e69 100644
--- a/results/irm/cvar_coverage_pq1.csv
+++ b/results/irm/cvar_coverage_pq1.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-LGBM,LGBM,0.9,0.9323076923076923,0.1908311409902022,0.04347081995558675,100
-LGBM,LGBM,0.95,0.9776923076923077,0.22738932956769187,0.04347081995558675,100
-LGBM,Logistic Regression,0.9,0.9146153846153847,0.1776482729176802,0.04405662937860094,100
-LGBM,Logistic Regression,0.95,0.9646153846153847,0.21168097338831957,0.04405662937860094,100
-Linear,LGBM,0.9,0.9307692307692308,0.21584587388672186,0.04750929738761366,100
-Linear,LGBM,0.95,0.9761538461538461,0.25719622226423833,0.04750929738761366,100
-Linear,Logistic Regression,0.9,0.8853846153846153,0.1934225485324801,0.04921876802543021,100
-Linear,Logistic Regression,0.95,0.943076923076923,0.23047718210904136,0.04921876802543021,100
+LGBM,LGBM,0.9,0.9323076923076923,0.1908311409902022,0.04358145932430658,100
+LGBM,LGBM,0.95,0.9776923076923077,0.22738932956769187,0.04358145932430658,100
+LGBM,Logistic Regression,0.9,0.9130769230769231,0.17764550716816235,0.04414608757632295,100
+LGBM,Logistic Regression,0.95,0.963076923076923,0.21167767779450106,0.04414608757632295,100
+Linear,LGBM,0.9,0.9292307692307692,0.21584587388672186,0.047457925834839765,100
+Linear,LGBM,0.95,0.9769230769230769,0.25719622226423833,0.047457925834839765,100
+Linear,Logistic Regression,0.9,0.8823076923076922,0.19342205011642188,0.0494625033437771,100
+Linear,Logistic Regression,0.95,0.9415384615384617,0.2304765882096771,0.0494625033437771,100
diff --git a/results/irm/cvar_coverage_qte.csv b/results/irm/cvar_coverage_qte.csv
index 4e413fe..2dbd870 100644
--- a/results/irm/cvar_coverage_qte.csv
+++ b/results/irm/cvar_coverage_qte.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
-LGBM,LGBM,0.9,0.9007692307692308,0.5818966962059838,0.14385931104084665,0.88,0.7055777033989438,100
-LGBM,LGBM,0.95,0.9492307692307692,0.693372679853793,0.14385931104084665,0.95,0.8113769406399532,100
-LGBM,Logistic Regression,0.9,0.8092307692307692,0.4171534550934474,0.12274374044729776,0.78,0.5062270696539016,100
-LGBM,Logistic Regression,0.95,0.87,0.49706900031277096,0.12274374044729776,0.86,0.5834562695237335,100
-Linear,LGBM,0.9,0.8007692307692308,0.6065907561805581,0.179698169022633,0.8,0.7182897195756133,100
-Linear,LGBM,0.95,0.8653846153846153,0.7227974671960807,0.179698169022633,0.85,0.8301176550726784,100
-Linear,Logistic Regression,0.9,0.7092307692307692,0.454167116768984,0.15248058466727346,0.69,0.5341820696542956,100
-Linear,Logistic Regression,0.95,0.8123076923076923,0.5411734985072126,0.15248058466727346,0.8,0.6185623415096295,100
+LGBM,LGBM,0.9,0.9038461538461539,0.5818966962059838,0.1435944755709475,0.88,0.7055777033989438,100
+LGBM,LGBM,0.95,0.9492307692307692,0.693372679853793,0.1435944755709475,0.94,0.8113769406399532,100
+LGBM,Logistic Regression,0.9,0.81,0.41716340917968886,0.12258144778601979,0.78,0.5062698827872832,100
+LGBM,Logistic Regression,0.95,0.8738461538461538,0.49708086133810014,0.12258144778601979,0.86,0.5835143322993298,100
+Linear,LGBM,0.9,0.8023076923076923,0.6065907561805581,0.1790914579109802,0.8,0.7182897195756133,100
+Linear,LGBM,0.95,0.8653846153846153,0.7227974671960807,0.1790914579109802,0.85,0.8301176550726784,100
+Linear,Logistic Regression,0.9,0.713076923076923,0.4541725983633358,0.15175636482362434,0.71,0.5341780882458428,100
+Linear,Logistic Regression,0.95,0.8146153846153846,0.541180030229751,0.15175636482362434,0.8,0.6185746229300051,100

From 69784400c8f010a059f9a5076a4151f862e7fac9 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 16:52:12 +0000
Subject: [PATCH 52/58] Update results from script:
 scripts/did/did_cs_atte_coverage.py

---
 results/did/did_cs_atte_coverage_metadata.csv | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/results/did/did_cs_atte_coverage_metadata.csv b/results/did/did_cs_atte_coverage_metadata.csv
index a29c07a..d6308e5 100644
--- a/results/did/did_cs_atte_coverage_metadata.csv
+++ b/results/did/did_cs_atte_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,did_cs_atte_coverage.py,2024-09-09 12:16:59,17588.891700983047,3.12.5
+0.10.dev0,did_cs_atte_coverage.py,2025-01-08 16:52:06,16598.133431196213,3.12.8

From 6ac7996443aa74b978dd90aa903a49daadd15186 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 17:13:20 +0000
Subject: [PATCH 53/58] Update results from script: scripts/irm/pq_coverage.py

---
 results/irm/pq_coverage_metadata.csv |  2 +-
 results/irm/pq_coverage_pq0.csv      | 16 ++++++++--------
 results/irm/pq_coverage_pq1.csv      | 16 ++++++++--------
 results/irm/pq_coverage_qte.csv      | 16 ++++++++--------
 4 files changed, 25 insertions(+), 25 deletions(-)

diff --git a/results/irm/pq_coverage_metadata.csv b/results/irm/pq_coverage_metadata.csv
index ca61794..17b95a8 100644
--- a/results/irm/pq_coverage_metadata.csv
+++ b/results/irm/pq_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,pq_coverage.py,2024-09-09 12:24:40,18061.192512512207,3.12.5
+0.10.dev0,pq_coverage.py,2025-01-08 17:13:20,17871.711226463318,3.12.8
diff --git a/results/irm/pq_coverage_pq0.csv b/results/irm/pq_coverage_pq0.csv
index 87e1c2c..c934b1a 100644
--- a/results/irm/pq_coverage_pq0.csv
+++ b/results/irm/pq_coverage_pq0.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-LGBM,LGBM,0.9,0.8823076923076922,0.5804011224570385,0.1491025005152581,100
-LGBM,LGBM,0.95,0.9346153846153846,0.6915905938151775,0.1491025005152581,100
-LGBM,Logistic Regression,0.9,0.8115384615384617,0.3861407256651673,0.11416614656762226,100
-LGBM,Logistic Regression,0.95,0.8861538461538462,0.46011505392766316,0.11416614656762226,100
-Logistic Regression,LGBM,0.9,0.8853846153846153,0.5879335180942484,0.15100690944933073,100
-Logistic Regression,LGBM,0.95,0.9415384615384617,0.7005659968080868,0.15100690944933073,100
-Logistic Regression,Logistic Regression,0.9,0.8223076923076923,0.38942866423036987,0.1123937956401062,100
-Logistic Regression,Logistic Regression,0.95,0.9015384615384616,0.46403287437416774,0.1123937956401062,100
+LGBM,LGBM,0.9,0.8838461538461538,0.5804011224570385,0.1489863706604989,100
+LGBM,LGBM,0.95,0.9353846153846154,0.6915905938151775,0.1489863706604989,100
+LGBM,Logistic Regression,0.9,0.8123076923076923,0.3860909559387072,0.11389794833419535,100
+LGBM,Logistic Regression,0.95,0.8876923076923078,0.46005574964077484,0.11389794833419535,100
+Logistic Regression,LGBM,0.9,0.8861538461538462,0.5879335180942487,0.1508479802166077,100
+Logistic Regression,LGBM,0.95,0.9423076923076923,0.7005659968080872,0.1508479802166077,100
+Logistic Regression,Logistic Regression,0.9,0.8246153846153846,0.3895072188527442,0.1120574898221174,100
+Logistic Regression,Logistic Regression,0.95,0.9046153846153847,0.4641264779800753,0.1120574898221174,100
diff --git a/results/irm/pq_coverage_pq1.csv b/results/irm/pq_coverage_pq1.csv
index 5e8e4fc..a56309b 100644
--- a/results/irm/pq_coverage_pq1.csv
+++ b/results/irm/pq_coverage_pq1.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-LGBM,LGBM,0.9,0.9130769230769231,0.2504138111093655,0.05865662571787472,100
-LGBM,LGBM,0.95,0.9623076923076923,0.298386460025268,0.05865662571787472,100
-LGBM,Logistic Regression,0.9,0.91,0.22948465548607,0.05375633654188718,100
-LGBM,Logistic Regression,0.95,0.9615384615384616,0.2734478329180528,0.05375633654188718,100
-Logistic Regression,LGBM,0.9,0.9192307692307692,0.25410039964172587,0.059363532936649595,100
-Logistic Regression,LGBM,0.95,0.9607692307692308,0.3027793012063014,0.059363532936649595,100
-Logistic Regression,Logistic Regression,0.9,0.8984615384615385,0.23093353063439134,0.057191896173723104,100
-Logistic Regression,Logistic Regression,0.95,0.9553846153846153,0.27517427414192513,0.057191896173723104,100
+LGBM,LGBM,0.9,0.9138461538461539,0.2504138111093655,0.058644803131633845,100
+LGBM,LGBM,0.95,0.9607692307692308,0.298386460025268,0.058644803131633845,100
+LGBM,Logistic Regression,0.9,0.9130769230769231,0.2294853436068611,0.05383096701300778,100
+LGBM,Logistic Regression,0.95,0.9623076923076923,0.2734486528645486,0.05383096701300778,100
+Logistic Regression,LGBM,0.9,0.916923076923077,0.25410039964172587,0.059305556876141904,100
+Logistic Regression,LGBM,0.95,0.9615384615384616,0.3027793012063014,0.059305556876141904,100
+Logistic Regression,Logistic Regression,0.9,0.8976923076923078,0.23093595343208725,0.057241427868032047,100
+Logistic Regression,Logistic Regression,0.95,0.9546153846153846,0.27517716108344265,0.057241427868032047,100
diff --git a/results/irm/pq_coverage_qte.csv b/results/irm/pq_coverage_qte.csv
index 4fea39b..a0fec02 100644
--- a/results/irm/pq_coverage_qte.csv
+++ b/results/irm/pq_coverage_qte.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
-LGBM,LGBM,0.9,0.8815384615384616,0.6176207568284253,0.15504772624658503,0.85,0.9336715877443045,100
-LGBM,LGBM,0.95,0.9407692307692308,0.7359405236146267,0.15504772624658503,0.91,1.0306538899948843,100
-LGBM,Logistic Regression,0.9,0.83,0.4257824194261344,0.12245088179297632,0.78,0.6460154145368233,100
-LGBM,Logistic Regression,0.95,0.9084615384615385,0.5073510454983309,0.12245088179297632,0.84,0.714250944722706,100
-Logistic Regression,LGBM,0.9,0.8961538461538461,0.6286198118927269,0.15900405481444213,0.87,0.9308233463178206,100
-Logistic Regression,LGBM,0.95,0.9484615384615386,0.7490467060960178,0.15900405481444213,0.92,1.0293001363085716,100
-Logistic Regression,Logistic Regression,0.9,0.8430769230769231,0.4344065634613077,0.12399216449911891,0.81,0.647334882587494,100
-Logistic Regression,Logistic Regression,0.95,0.9115384615384616,0.5176273469451368,0.12399216449911891,0.86,0.7197477669291079,100
+LGBM,LGBM,0.9,0.8815384615384616,0.6176207568284253,0.15515498246785267,0.85,0.9336715877443045,100
+LGBM,LGBM,0.95,0.94,0.7359405236146267,0.15515498246785267,0.91,1.0306538899948843,100
+LGBM,Logistic Regression,0.9,0.826923076923077,0.4257337159670842,0.122640423715187,0.78,0.6459408206266708,100
+LGBM,Logistic Regression,0.95,0.9092307692307692,0.5072930117474264,0.122640423715187,0.84,0.7141895123082023,100
+Logistic Regression,LGBM,0.9,0.8969230769230769,0.6286198118927271,0.15916890224887578,0.87,0.9308233463178209,100
+Logistic Regression,LGBM,0.95,0.946923076923077,0.7490467060960181,0.15916890224887578,0.92,1.029300136308572,100
+Logistic Regression,Logistic Regression,0.9,0.8407692307692308,0.43448201352405663,0.12418740801387926,0.81,0.6474698211016049,100
+Logistic Regression,Logistic Regression,0.95,0.9123076923076923,0.5177172512400822,0.12418740801387926,0.85,0.719895714650183,100

From 47ee870997e8193fb4f24ccc2598d1054a180836 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 17:24:34 +0000
Subject: [PATCH 54/58] Update results from script: scripts/irm/lpq_coverage.py

---
 results/irm/lpq_coverage_lpq0.csv     | 16 ++++++++--------
 results/irm/lpq_coverage_lpq1.csv     | 16 ++++++++--------
 results/irm/lpq_coverage_lqte.csv     | 16 ++++++++--------
 results/irm/lpq_coverage_metadata.csv |  2 +-
 4 files changed, 25 insertions(+), 25 deletions(-)

diff --git a/results/irm/lpq_coverage_lpq0.csv b/results/irm/lpq_coverage_lpq0.csv
index 8df271f..566dd1f 100644
--- a/results/irm/lpq_coverage_lpq0.csv
+++ b/results/irm/lpq_coverage_lpq0.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-LGBM,LGBM,0.9,0.94,1.1717023704378204,0.23183406397860207,100
-LGBM,LGBM,0.95,0.9733333333333333,1.396169488293374,0.23183406397860207,100
-LGBM,Logistic Regression,0.9,0.95,1.124933562445929,0.2275644497861777,100
-LGBM,Logistic Regression,0.95,0.9766666666666667,1.3404410163114224,0.2275644497861777,100
-Logistic Regression,LGBM,0.9,0.9477777777777777,1.1516756381210262,0.22097742768241296,100
-Logistic Regression,LGBM,0.95,0.9811111111111112,1.3723061648791872,0.22097742768241296,100
-Logistic Regression,Logistic Regression,0.9,0.9533333333333333,1.1085912475488997,0.20668700656290437,100
-Logistic Regression,Logistic Regression,0.95,0.9788888888888888,1.3209679470380462,0.20668700656290437,100
+LGBM,LGBM,0.9,0.94,1.1717023704378204,0.23177376824257415,100
+LGBM,LGBM,0.95,0.9722222222222223,1.396169488293374,0.23177376824257415,100
+LGBM,Logistic Regression,0.9,0.95,1.1248327860637255,0.2271354130168218,100
+LGBM,Logistic Regression,0.95,0.9755555555555556,1.3403209338454969,0.2271354130168218,100
+Logistic Regression,LGBM,0.9,0.95,1.1516756381210271,0.22092321662449366,100
+Logistic Regression,LGBM,0.95,0.9811111111111112,1.372306164879188,0.22092321662449366,100
+Logistic Regression,Logistic Regression,0.9,0.9533333333333333,1.1095156391492578,0.20615547550299898,100
+Logistic Regression,Logistic Regression,0.95,0.9788888888888888,1.3220694275677582,0.20615547550299898,100
diff --git a/results/irm/lpq_coverage_lpq1.csv b/results/irm/lpq_coverage_lpq1.csv
index 6bfc9b2..ba57b07 100644
--- a/results/irm/lpq_coverage_lpq1.csv
+++ b/results/irm/lpq_coverage_lpq1.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-LGBM,LGBM,0.9,0.9577777777777777,1.6624989751251327,0.32794811978077126,100
-LGBM,LGBM,0.95,0.99,1.9809897137285786,0.32794811978077126,100
-LGBM,Logistic Regression,0.9,0.94,1.589606393126724,0.3222751957636039,100
-LGBM,Logistic Regression,0.95,0.97,1.8941328450588726,0.3222751957636039,100
-Logistic Regression,LGBM,0.9,0.96,1.6078485820230732,0.3009359326740972,100
-Logistic Regression,LGBM,0.95,0.9822222222222223,1.9158697538331122,0.3009359326740972,100
-Logistic Regression,Logistic Regression,0.9,0.9466666666666668,1.5564190145145989,0.3055460305222601,100
-Logistic Regression,Logistic Regression,0.95,0.9844444444444445,1.8545876443460196,0.3055460305222601,100
+LGBM,LGBM,0.9,0.9577777777777777,1.6624989751251327,0.32781267630898475,100
+LGBM,LGBM,0.95,0.99,1.9809897137285786,0.32781267630898475,100
+LGBM,Logistic Regression,0.9,0.9411111111111111,1.5914676830888603,0.32199246221295674,100
+LGBM,Logistic Regression,0.95,0.97,1.8963507088437095,0.32199246221295674,100
+Logistic Regression,LGBM,0.9,0.96,1.60784858202307,0.30086810092875493,100
+Logistic Regression,LGBM,0.95,0.9822222222222223,1.915869753833108,0.30086810092875493,100
+Logistic Regression,Logistic Regression,0.9,0.9477777777777777,1.5561898364166578,0.30507352946060423,100
+Logistic Regression,Logistic Regression,0.95,0.9844444444444445,1.854314561798947,0.30507352946060423,100
diff --git a/results/irm/lpq_coverage_lqte.csv b/results/irm/lpq_coverage_lqte.csv
index 31322fc..4edaa4e 100644
--- a/results/irm/lpq_coverage_lqte.csv
+++ b/results/irm/lpq_coverage_lqte.csv
@@ -1,9 +1,9 @@
 Learner g,Learner m,level,Coverage,CI Length,Bias,Uniform Coverage,Uniform CI Length,repetition
-LGBM,LGBM,0.9,0.9233333333333333,1.636872420792144,0.38509449105953003,0.94,2.2547716211801454,100
-LGBM,LGBM,0.95,0.9633333333333333,1.950453790824845,0.38509449105953003,0.97,2.5400452907969764,100
-LGBM,Logistic Regression,0.9,0.91,1.5657795728691977,0.37487491739204254,0.9,2.154808632448696,100
-LGBM,Logistic Regression,0.95,0.9488888888888889,1.8657414375769725,0.37487491739204254,0.95,2.424204209936085,100
-Logistic Regression,LGBM,0.9,0.9188888888888889,1.6190226009242594,0.3724923151955094,0.92,2.208051172256097,100
-Logistic Regression,LGBM,0.95,0.9644444444444444,1.9291844185850662,0.3724923151955094,0.98,2.487384422889674,100
-Logistic Regression,Logistic Regression,0.9,0.9033333333333333,1.563967614483271,0.37277891050263284,0.9,2.13603227354138,100
-Logistic Regression,Logistic Regression,0.95,0.9488888888888889,1.8635823559907991,0.37277891050263284,0.95,2.4084686120659855,100
+LGBM,LGBM,0.9,0.9233333333333333,1.636872420792144,0.3849163075483558,0.94,2.2547716211801454,100
+LGBM,LGBM,0.95,0.9633333333333333,1.950453790824845,0.3849163075483558,0.97,2.5400452907969764,100
+LGBM,Logistic Regression,0.9,0.9077777777777777,1.5675486277219108,0.3750309062078869,0.91,2.157430608143212,100
+LGBM,Logistic Regression,0.95,0.95,1.8678493964501393,0.3750309062078869,0.95,2.4273382603132627,100
+Logistic Regression,LGBM,0.9,0.9188888888888889,1.6190226009242576,0.3723079594843724,0.92,2.208051172256097,100
+Logistic Regression,LGBM,0.95,0.9644444444444444,1.9291844185850642,0.3723079594843724,0.98,2.4873844228896727,100
+Logistic Regression,Logistic Regression,0.9,0.9077777777777777,1.564249778556274,0.37200263232334746,0.9,2.1368366984439215,100
+Logistic Regression,Logistic Regression,0.95,0.9477777777777777,1.8639185752213465,0.37200263232334746,0.95,2.4083334749081065,100
diff --git a/results/irm/lpq_coverage_metadata.csv b/results/irm/lpq_coverage_metadata.csv
index 8571998..63994d8 100644
--- a/results/irm/lpq_coverage_metadata.csv
+++ b/results/irm/lpq_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,lpq_coverage.py,2024-09-09 12:37:02,18799.444734811783,3.12.5
+0.10.dev0,lpq_coverage.py,2025-01-08 17:24:33,18545.282371282578,3.12.8

From 5d6db9c3638b52f04321ab2759d4e6a881e70eee Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 17:31:20 +0000
Subject: [PATCH 55/58] Update results from script:
 scripts/rdd/rdd_fuzzy_coverage.py

---
 results/rdd/rdd_fuzzy_coverage.csv          | 28 ++++++++++-----------
 results/rdd/rdd_fuzzy_coverage_metadata.csv |  2 +-
 2 files changed, 15 insertions(+), 15 deletions(-)

diff --git a/results/rdd/rdd_fuzzy_coverage.csv b/results/rdd/rdd_fuzzy_coverage.csv
index 2326df5..70f4810 100644
--- a/results/rdd/rdd_fuzzy_coverage.csv
+++ b/results/rdd/rdd_fuzzy_coverage.csv
@@ -13,8 +13,8 @@ rdflex,cutoff,LGBM,LGBM,0.9,0.9299065420560748,2.0440609614236096,0.506204805500
 rdflex,cutoff,LGBM,LGBM,0.95,0.9719626168224299,2.4356488631877444,0.5062048055000609,214
 rdflex,cutoff,LGBM,Linear,0.9,0.9532710280373832,2.082858834410821,0.4862344864688502,214
 rdflex,cutoff,LGBM,Linear,0.95,0.9906542056074766,2.481879380290126,0.4862344864688502,214
-rdflex,cutoff,LGBM,Stacked,0.9,0.9065420560747663,2.019090300402747,0.47574061346930346,214
-rdflex,cutoff,LGBM,Stacked,0.95,0.9672897196261683,2.4058944853700925,0.47574061346930346,214
+rdflex,cutoff,LGBM,Stacked,0.9,0.9065420560747663,2.019090300402747,0.4757406134693035,214
+rdflex,cutoff,LGBM,Stacked,0.95,0.9672897196261683,2.4058944853700925,0.4757406134693035,214
 rdflex,cutoff,Linear,Global linear,0.9,0.9439252336448598,10.55612712298056,2.5518911139757785,214
 rdflex,cutoff,Linear,Global linear,0.95,0.9766355140186916,12.578401286449983,2.5518911139757785,214
 rdflex,cutoff,Linear,LGBM,0.9,0.9439252336448598,10.761495324878737,2.639346775020516,214
@@ -29,8 +29,8 @@ rdflex,cutoff,Stacked,LGBM,0.9,0.9485981308411215,1.9952932413270021,0.465436781
 rdflex,cutoff,Stacked,LGBM,0.95,0.9906542056074766,2.3775385405235743,0.4654367817416753,214
 rdflex,cutoff,Stacked,Linear,0.9,0.9392523364485982,2.1078303244900973,0.45375955245086014,214
 rdflex,cutoff,Stacked,Linear,0.95,0.9813084112149533,2.5116347459918087,0.45375955245086014,214
-rdflex,cutoff,Stacked,Stacked,0.9,0.9392523364485982,2.0202332872592588,0.4453107509428898,214
-rdflex,cutoff,Stacked,Stacked,0.95,0.9719626168224299,2.407256438213105,0.4453107509428898,214
+rdflex,cutoff,Stacked,Stacked,0.9,0.9392523364485982,2.0202332872592588,0.4453107509428897,214
+rdflex,cutoff,Stacked,Stacked,0.95,0.9719626168224299,2.407256438213105,0.4453107509428897,214
 rdflex,cutoff and score,Global linear,Global linear,0.9,0.9439252336448598,10.545901405614005,2.5648476809096707,214
 rdflex,cutoff and score,Global linear,Global linear,0.95,0.9766355140186916,12.56621659267168,2.5648476809096707,214
 rdflex,cutoff and score,Global linear,LGBM,0.9,0.9439252336448598,10.795739229679457,2.6380721682853405,214
@@ -45,40 +45,40 @@ rdflex,cutoff and score,LGBM,LGBM,0.9,0.9392523364485982,2.1973662757190073,0.53
 rdflex,cutoff and score,LGBM,LGBM,0.95,0.9672897196261683,2.6183234122991212,0.5327660380926273,214
 rdflex,cutoff and score,LGBM,Linear,0.9,0.9439252336448598,2.198701801510649,0.478151037013903,214
 rdflex,cutoff and score,LGBM,Linear,0.95,0.9766355140186916,2.619914789433933,0.478151037013903,214
-rdflex,cutoff and score,LGBM,Stacked,0.9,0.9626168224299065,2.1339233144534187,0.5089928094483224,214
-rdflex,cutoff and score,LGBM,Stacked,0.95,0.9813084112149533,2.542726461229631,0.5089928094483224,214
+rdflex,cutoff and score,LGBM,Stacked,0.9,0.9626168224299065,2.134004257981735,0.5088647456589316,214
+rdflex,cutoff and score,LGBM,Stacked,0.95,0.9813084112149533,2.542822911392541,0.5088647456589316,214
 rdflex,cutoff and score,Linear,Global linear,0.9,0.9299065420560748,10.644692713092242,2.598861379899407,214
 rdflex,cutoff and score,Linear,Global linear,0.95,0.9766355140186916,12.683933696169714,2.598861379899407,214
 rdflex,cutoff and score,Linear,LGBM,0.9,0.9532710280373832,10.854187936587056,2.7014940383227355,214
 rdflex,cutoff and score,Linear,LGBM,0.95,0.985981308411215,12.933562651752837,2.7014940383227355,214
 rdflex,cutoff and score,Linear,Linear,0.9,0.9252336448598131,10.724343356023862,2.5881292715569817,214
 rdflex,cutoff and score,Linear,Linear,0.95,0.9766355140186916,12.77884329112302,2.5881292715569817,214
-rdflex,cutoff and score,Linear,Stacked,0.9,0.9345794392523364,10.776895897775766,2.6499533364372025,214
-rdflex,cutoff and score,Linear,Stacked,0.95,0.9719626168224299,12.841463506953815,2.6499533364372025,214
+rdflex,cutoff and score,Linear,Stacked,0.9,0.9345794392523364,10.777399597744738,2.6500175292018375,214
+rdflex,cutoff and score,Linear,Stacked,0.95,0.9719626168224299,12.842063702486124,2.6500175292018375,214
 rdflex,cutoff and score,Stacked,Global linear,0.9,0.9252336448598131,2.1786088679569744,0.4966485703629167,214
 rdflex,cutoff and score,Stacked,Global linear,0.95,0.9719626168224299,2.5959725823805626,0.4966485703629167,214
 rdflex,cutoff and score,Stacked,LGBM,0.9,0.9485981308411215,2.1461144187284016,0.4942766032999762,214
 rdflex,cutoff and score,Stacked,LGBM,0.95,0.9672897196261683,2.557253057954851,0.4942766032999762,214
 rdflex,cutoff and score,Stacked,Linear,0.9,0.9439252336448598,2.213911931815932,0.5031341173016854,214
 rdflex,cutoff and score,Stacked,Linear,0.95,0.9906542056074766,2.638038777556674,0.5031341173016854,214
-rdflex,cutoff and score,Stacked,Stacked,0.9,0.9579439252336449,2.2524280242253742,0.49230022385126054,214
-rdflex,cutoff and score,Stacked,Stacked,0.95,0.9813084112149533,2.683933532391263,0.49230022385126054,214
+rdflex,cutoff and score,Stacked,Stacked,0.9,0.9579439252336449,2.2523882384073124,0.49263083446339334,214
+rdflex,cutoff and score,Stacked,Stacked,0.95,0.9813084112149533,2.683886124664996,0.49263083446339334,214
 rdflex,interacted cutoff and score,Global linear,Global linear,0.9,0.9439252336448598,10.533084606204715,2.536539354378303,214
 rdflex,interacted cutoff and score,Global linear,Global linear,0.95,0.9766355140186916,12.550944434208654,2.536539354378303,214
 rdflex,interacted cutoff and score,Global linear,LGBM,0.9,0.9485981308411215,10.889767355232552,2.662636398748481,214
 rdflex,interacted cutoff and score,Global linear,LGBM,0.95,0.9813084112149533,12.975958143967722,2.662636398748481,214
 rdflex,interacted cutoff and score,Global linear,Linear,0.9,0.9485981308411215,10.68507130374861,2.586187139044067,214
 rdflex,interacted cutoff and score,Global linear,Linear,0.95,0.9766355140186916,12.732047754549267,2.586187139044067,214
-rdflex,interacted cutoff and score,Global linear,Stacked,0.9,0.9439252336448598,10.558833608328598,2.603031338515077,214
-rdflex,interacted cutoff and score,Global linear,Stacked,0.95,0.9719626168224299,12.581626262654503,2.603031338515077,214
+rdflex,interacted cutoff and score,Global linear,Stacked,0.9,0.9439252336448598,10.558703379952977,2.603058464158783,214
+rdflex,interacted cutoff and score,Global linear,Stacked,0.95,0.9719626168224299,12.581471085973858,2.603058464158783,214
 rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.9392523364485982,2.142350464078299,0.4962040631698678,214
 rdflex,interacted cutoff and score,LGBM,Global linear,0.95,0.9813084112149533,2.5527680293585275,0.4962040631698678,214
 rdflex,interacted cutoff and score,LGBM,LGBM,0.9,0.9439252336448598,2.248059401902932,0.5371172689574487,214
 rdflex,interacted cutoff and score,LGBM,LGBM,0.95,0.9813084112149533,2.6787279978234766,0.5371172689574487,214
 rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.9299065420560748,2.2069200480948767,0.5204804556154995,214
 rdflex,interacted cutoff and score,LGBM,Linear,0.95,0.985981308411215,2.6297074342366247,0.5204804556154995,214
-rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.9439252336448598,2.1299774006239818,0.5255852225079005,214
-rdflex,interacted cutoff and score,LGBM,Stacked,0.95,0.985981308411215,2.5380246148980956,0.5255852225079005,214
+rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.9439252336448598,2.1300404990101094,0.526283843809854,214
+rdflex,interacted cutoff and score,LGBM,Stacked,0.95,0.985981308411215,2.5380998012625637,0.526283843809854,214
 rdflex,interacted cutoff and score,Linear,Global linear,0.9,0.9345794392523364,10.68120559444222,2.6167228434568193,214
 rdflex,interacted cutoff and score,Linear,Global linear,0.95,0.9766355140186916,12.727441477801555,2.6167228434568193,214
 rdflex,interacted cutoff and score,Linear,LGBM,0.9,0.9485981308411215,11.082779264157297,2.7433028249989375,214
diff --git a/results/rdd/rdd_fuzzy_coverage_metadata.csv b/results/rdd/rdd_fuzzy_coverage_metadata.csv
index 3322990..3fc4f25 100644
--- a/results/rdd/rdd_fuzzy_coverage_metadata.csv
+++ b/results/rdd/rdd_fuzzy_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_fuzzy_coverage.py,2025-01-07 18:31:42,19889.126134634018,3.12.8
+0.9.dev0,rdd_fuzzy_coverage.py,2025-01-08 17:31:20,19870.016520500183,3.12.8

From eeba30d95c49b7d33f42f7e650ca316ba62d72f6 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 17:35:01 +0000
Subject: [PATCH 56/58] Update results from script:
 scripts/plm/pliv_late_coverage.py

---
 results/plm/pliv_late_coverage.csv          | 56 ++++++++++-----------
 results/plm/pliv_late_coverage_metadata.csv |  2 +-
 2 files changed, 29 insertions(+), 29 deletions(-)

diff --git a/results/plm/pliv_late_coverage.csv b/results/plm/pliv_late_coverage.csv
index 0482f22..eec541b 100644
--- a/results/plm/pliv_late_coverage.csv
+++ b/results/plm/pliv_late_coverage.csv
@@ -3,31 +3,31 @@ Lasso,Lasso,Lasso,IV-type,0.9,0.806,0.23181691237656843,0.071516051616331,1000
 Lasso,Lasso,Lasso,IV-type,0.95,0.873,0.2762268884116072,0.071516051616331,1000
 Lasso,Lasso,Lasso,partialling out,0.9,0.899,0.2994589442321557,0.07151348023026591,1000
 Lasso,Lasso,Lasso,partialling out,0.95,0.947,0.35682734069852273,0.07151348023026591,1000
-Lasso,Lasso,Random Forest,IV-type,0.9,0.806,0.23192478502357472,0.07187026721767026,1000
-Lasso,Lasso,Random Forest,IV-type,0.95,0.865,0.2763554265985832,0.07187026721767026,1000
-Lasso,Lasso,Random Forest,partialling out,0.9,0.896,0.3068383735438992,0.0741569646182831,1000
-Lasso,Lasso,Random Forest,partialling out,0.95,0.947,0.3656204730724243,0.0741569646182831,1000
-Lasso,Random Forest,Lasso,IV-type,0.9,0.83,0.2644292585766018,0.07753973367612393,1000
-Lasso,Random Forest,Lasso,IV-type,0.95,0.901,0.3150868957436169,0.07753973367612393,1000
-Lasso,Random Forest,Lasso,partialling out,0.9,0.904,0.3173435440931062,0.07691371311292067,1000
-Lasso,Random Forest,Lasso,partialling out,0.95,0.956,0.3781381558561849,0.07691371311292067,1000
-Lasso,Random Forest,Random Forest,IV-type,0.9,0.838,0.26484483955141147,0.07664037514487268,1000
-Lasso,Random Forest,Random Forest,IV-type,0.95,0.909,0.31558209101810264,0.07664037514487268,1000
-Lasso,Random Forest,Random Forest,partialling out,0.9,0.876,0.3009573997300998,0.08173024901795378,1000
-Lasso,Random Forest,Random Forest,partialling out,0.95,0.943,0.3586128605528636,0.08173024901795378,1000
-Random Forest,Lasso,Lasso,IV-type,0.9,0.792,0.24229814878232575,0.07640585085746515,1000
-Random Forest,Lasso,Lasso,IV-type,0.95,0.867,0.28871605190441474,0.07640585085746515,1000
-Random Forest,Lasso,Lasso,partialling out,0.9,0.908,0.3309481527556741,0.08063082596936634,1000
-Random Forest,Lasso,Lasso,partialling out,0.95,0.952,0.39434904694429584,0.08063082596936634,1000
-Random Forest,Lasso,Random Forest,IV-type,0.9,0.802,0.24169974855188303,0.07499899652306129,1000
-Random Forest,Lasso,Random Forest,IV-type,0.95,0.875,0.28800301405059553,0.07499899652306129,1000
-Random Forest,Lasso,Random Forest,partialling out,0.9,0.912,0.31892872567199654,0.07590450344220336,1000
-Random Forest,Lasso,Random Forest,partialling out,0.95,0.958,0.3800270162098806,0.07590450344220336,1000
-Random Forest,Random Forest,Lasso,IV-type,0.9,0.826,0.27840682771822006,0.07984522594527775,1000
-Random Forest,Random Forest,Lasso,IV-type,0.95,0.888,0.33174219665313587,0.07984522594527775,1000
-Random Forest,Random Forest,Lasso,partialling out,0.9,0.79,0.35115828845926267,0.10762971655091783,1000
-Random Forest,Random Forest,Lasso,partialling out,0.95,0.865,0.4184309089730254,0.10762971655091783,1000
-Random Forest,Random Forest,Random Forest,IV-type,0.9,0.822,0.27425117516011144,0.07888472952601593,1000
-Random Forest,Random Forest,Random Forest,IV-type,0.95,0.893,0.32679043121170237,0.07888472952601593,1000
-Random Forest,Random Forest,Random Forest,partialling out,0.9,0.874,0.30385637054427705,0.07807502303728009,1000
-Random Forest,Random Forest,Random Forest,partialling out,0.95,0.93,0.3620671973369523,0.07807502303728009,1000
+Lasso,Lasso,Random Forest,IV-type,0.9,0.808,0.23192003415034532,0.07189717055113612,1000
+Lasso,Lasso,Random Forest,IV-type,0.95,0.866,0.27634976558396634,0.07189717055113612,1000
+Lasso,Lasso,Random Forest,partialling out,0.9,0.899,0.306946616292115,0.0739728160311134,1000
+Lasso,Lasso,Random Forest,partialling out,0.95,0.947,0.365749452262192,0.0739728160311134,1000
+Lasso,Random Forest,Lasso,IV-type,0.9,0.83,0.2641727277684909,0.07763295491460846,1000
+Lasso,Random Forest,Lasso,IV-type,0.95,0.9,0.31478122043209744,0.07763295491460846,1000
+Lasso,Random Forest,Lasso,partialling out,0.9,0.906,0.31724103561902756,0.07721936392175144,1000
+Lasso,Random Forest,Lasso,partialling out,0.95,0.952,0.3780160094754904,0.07721936392175144,1000
+Lasso,Random Forest,Random Forest,IV-type,0.9,0.834,0.2647124176667093,0.07680126322014207,1000
+Lasso,Random Forest,Random Forest,IV-type,0.95,0.914,0.31542430061017296,0.07680126322014207,1000
+Lasso,Random Forest,Random Forest,partialling out,0.9,0.874,0.3008847110321322,0.08096376656362451,1000
+Lasso,Random Forest,Random Forest,partialling out,0.95,0.948,0.358526246627001,0.08096376656362451,1000
+Random Forest,Lasso,Lasso,IV-type,0.9,0.797,0.24216323960269195,0.07658572792546856,1000
+Random Forest,Lasso,Lasso,IV-type,0.95,0.864,0.2885552977017711,0.07658572792546856,1000
+Random Forest,Lasso,Lasso,partialling out,0.9,0.905,0.33082304355897396,0.08047007130194417,1000
+Random Forest,Lasso,Lasso,partialling out,0.95,0.954,0.3941999701415645,0.08047007130194417,1000
+Random Forest,Lasso,Random Forest,IV-type,0.9,0.802,0.24165696675117043,0.07510539234046823,1000
+Random Forest,Lasso,Random Forest,IV-type,0.95,0.878,0.28795203639081074,0.07510539234046823,1000
+Random Forest,Lasso,Random Forest,partialling out,0.9,0.905,0.31918216721413517,0.07671818026815334,1000
+Random Forest,Lasso,Random Forest,partialling out,0.95,0.949,0.3803290104339495,0.07671818026815334,1000
+Random Forest,Random Forest,Lasso,IV-type,0.9,0.828,0.27855600069164016,0.0798644714171535,1000
+Random Forest,Random Forest,Lasso,IV-type,0.95,0.894,0.33191994721438917,0.0798644714171535,1000
+Random Forest,Random Forest,Lasso,partialling out,0.9,0.792,0.35144455288760573,0.1068047543860758,1000
+Random Forest,Random Forest,Lasso,partialling out,0.95,0.862,0.418772014078315,0.1068047543860758,1000
+Random Forest,Random Forest,Random Forest,IV-type,0.9,0.819,0.27446473521048453,0.07996992581732235,1000
+Random Forest,Random Forest,Random Forest,IV-type,0.95,0.889,0.3270449037072543,0.07996992581732235,1000
+Random Forest,Random Forest,Random Forest,partialling out,0.9,0.866,0.30400744761250564,0.07843878847708105,1000
+Random Forest,Random Forest,Random Forest,partialling out,0.95,0.926,0.3622472167671108,0.07843878847708105,1000
diff --git a/results/plm/pliv_late_coverage_metadata.csv b/results/plm/pliv_late_coverage_metadata.csv
index d631247..37383e7 100644
--- a/results/plm/pliv_late_coverage_metadata.csv
+++ b/results/plm/pliv_late_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.0,pliv_late_coverage.py,2024-09-09 12:44:11,19234.77849960327,3.12.5
+0.10.dev0,pliv_late_coverage.py,2025-01-08 17:34:57,19185.31809258461,3.12.8

From 6c6b5d13c362bbb33041fdac4ac78273e50eaf49 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 19:08:44 +0000
Subject: [PATCH 57/58] Update results from script:
 scripts/rdd/rdd_sharp_coverage.py

---
 results/rdd/rdd_sharp_coverage_metadata.csv | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/results/rdd/rdd_sharp_coverage_metadata.csv b/results/rdd/rdd_sharp_coverage_metadata.csv
index 8e3ce8d..8d0e821 100644
--- a/results/rdd/rdd_sharp_coverage_metadata.csv
+++ b/results/rdd/rdd_sharp_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_sharp_coverage.py,2025-01-08 13:08:54,4129.017676591873,3.12.8
+0.9.dev0,rdd_sharp_coverage.py,2025-01-08 19:08:43,4069.1944484710693,3.12.8

From 7c861f55df18a94eb8d06b5fe2993f46bb0e07b1 Mon Sep 17 00:00:00 2001
From: github-actions <github-actions@github.com>
Date: Wed, 8 Jan 2025 23:31:58 +0000
Subject: [PATCH 58/58] Update results from script:
 scripts/rdd/rdd_fuzzy_coverage.py

---
 results/rdd/rdd_fuzzy_coverage.csv          | 196 ++++++++++----------
 results/rdd/rdd_fuzzy_coverage_metadata.csv |   2 +-
 2 files changed, 99 insertions(+), 99 deletions(-)

diff --git a/results/rdd/rdd_fuzzy_coverage.csv b/results/rdd/rdd_fuzzy_coverage.csv
index 70f4810..053bed7 100644
--- a/results/rdd/rdd_fuzzy_coverage.csv
+++ b/results/rdd/rdd_fuzzy_coverage.csv
@@ -1,99 +1,99 @@
 Method,fs specification,Learner g,Learner m,level,Coverage,CI Length,Bias,repetition
-rdflex,cutoff,Global linear,Global linear,0.9,0.9439252336448598,10.555050121998914,2.557454881202291,214
-rdflex,cutoff,Global linear,Global linear,0.95,0.9766355140186916,12.577117960626483,2.557454881202291,214
-rdflex,cutoff,Global linear,LGBM,0.9,0.9439252336448598,10.714048740732457,2.6261561018337476,214
-rdflex,cutoff,Global linear,LGBM,0.95,0.9813084112149533,12.766576500403625,2.6261561018337476,214
-rdflex,cutoff,Global linear,Linear,0.9,0.9392523364485982,10.69861124776851,2.6084394390564283,214
-rdflex,cutoff,Global linear,Linear,0.95,0.9766355140186916,12.748181592963135,2.6084394390564283,214
-rdflex,cutoff,Global linear,Stacked,0.9,0.9485981308411215,10.542991289273992,2.6322225801086323,214
-rdflex,cutoff,Global linear,Stacked,0.95,0.9719626168224299,12.562748975174422,2.6322225801086323,214
-rdflex,cutoff,LGBM,Global linear,0.9,0.9345794392523364,2.029337501353004,0.4700006325418856,214
-rdflex,cutoff,LGBM,Global linear,0.95,0.9672897196261683,2.4181047784173058,0.4700006325418856,214
-rdflex,cutoff,LGBM,LGBM,0.9,0.9299065420560748,2.0440609614236096,0.5062048055000609,214
-rdflex,cutoff,LGBM,LGBM,0.95,0.9719626168224299,2.4356488631877444,0.5062048055000609,214
-rdflex,cutoff,LGBM,Linear,0.9,0.9532710280373832,2.082858834410821,0.4862344864688502,214
-rdflex,cutoff,LGBM,Linear,0.95,0.9906542056074766,2.481879380290126,0.4862344864688502,214
-rdflex,cutoff,LGBM,Stacked,0.9,0.9065420560747663,2.019090300402747,0.4757406134693035,214
-rdflex,cutoff,LGBM,Stacked,0.95,0.9672897196261683,2.4058944853700925,0.4757406134693035,214
-rdflex,cutoff,Linear,Global linear,0.9,0.9439252336448598,10.55612712298056,2.5518911139757785,214
-rdflex,cutoff,Linear,Global linear,0.95,0.9766355140186916,12.578401286449983,2.5518911139757785,214
-rdflex,cutoff,Linear,LGBM,0.9,0.9439252336448598,10.761495324878737,2.639346775020516,214
-rdflex,cutoff,Linear,LGBM,0.95,0.9766355140186916,12.823112592486487,2.639346775020516,214
-rdflex,cutoff,Linear,Linear,0.9,0.9345794392523364,10.748611527983986,2.614648978480689,214
-rdflex,cutoff,Linear,Linear,0.95,0.9766355140186916,12.807760601595577,2.614648978480689,214
-rdflex,cutoff,Linear,Stacked,0.9,0.9439252336448598,10.400228114739594,2.5119733327212943,214
-rdflex,cutoff,Linear,Stacked,0.95,0.9766355140186916,12.392636160379698,2.5119733327212943,214
-rdflex,cutoff,Stacked,Global linear,0.9,0.9299065420560748,2.100352405285733,0.4993647885601086,214
-rdflex,cutoff,Stacked,Global linear,0.95,0.9719626168224299,2.502724255672364,0.4993647885601086,214
-rdflex,cutoff,Stacked,LGBM,0.9,0.9485981308411215,1.9952932413270021,0.4654367817416753,214
-rdflex,cutoff,Stacked,LGBM,0.95,0.9906542056074766,2.3775385405235743,0.4654367817416753,214
-rdflex,cutoff,Stacked,Linear,0.9,0.9392523364485982,2.1078303244900973,0.45375955245086014,214
-rdflex,cutoff,Stacked,Linear,0.95,0.9813084112149533,2.5116347459918087,0.45375955245086014,214
-rdflex,cutoff,Stacked,Stacked,0.9,0.9392523364485982,2.0202332872592588,0.4453107509428897,214
-rdflex,cutoff,Stacked,Stacked,0.95,0.9719626168224299,2.407256438213105,0.4453107509428897,214
-rdflex,cutoff and score,Global linear,Global linear,0.9,0.9439252336448598,10.545901405614005,2.5648476809096707,214
-rdflex,cutoff and score,Global linear,Global linear,0.95,0.9766355140186916,12.56621659267168,2.5648476809096707,214
-rdflex,cutoff and score,Global linear,LGBM,0.9,0.9439252336448598,10.795739229679457,2.6380721682853405,214
-rdflex,cutoff and score,Global linear,LGBM,0.95,0.9813084112149533,12.863916721802127,2.6380721682853405,214
-rdflex,cutoff and score,Global linear,Linear,0.9,0.9439252336448598,10.722039462420188,2.601946990911434,214
-rdflex,cutoff and score,Global linear,Linear,0.95,0.9766355140186916,12.776098032570266,2.601946990911434,214
-rdflex,cutoff and score,Global linear,Stacked,0.9,0.9485981308411215,10.84957752003617,2.6393360419176215,214
-rdflex,cutoff and score,Global linear,Stacked,0.95,0.9766355140186916,12.928069001591265,2.6393360419176215,214
-rdflex,cutoff and score,LGBM,Global linear,0.9,0.9532710280373832,2.1553015781124825,0.4985124204199334,214
-rdflex,cutoff and score,LGBM,Global linear,0.95,0.9813084112149533,2.5682002335685254,0.4985124204199334,214
-rdflex,cutoff and score,LGBM,LGBM,0.9,0.9392523364485982,2.1973662757190073,0.5327660380926273,214
-rdflex,cutoff and score,LGBM,LGBM,0.95,0.9672897196261683,2.6183234122991212,0.5327660380926273,214
-rdflex,cutoff and score,LGBM,Linear,0.9,0.9439252336448598,2.198701801510649,0.478151037013903,214
-rdflex,cutoff and score,LGBM,Linear,0.95,0.9766355140186916,2.619914789433933,0.478151037013903,214
-rdflex,cutoff and score,LGBM,Stacked,0.9,0.9626168224299065,2.134004257981735,0.5088647456589316,214
-rdflex,cutoff and score,LGBM,Stacked,0.95,0.9813084112149533,2.542822911392541,0.5088647456589316,214
-rdflex,cutoff and score,Linear,Global linear,0.9,0.9299065420560748,10.644692713092242,2.598861379899407,214
-rdflex,cutoff and score,Linear,Global linear,0.95,0.9766355140186916,12.683933696169714,2.598861379899407,214
-rdflex,cutoff and score,Linear,LGBM,0.9,0.9532710280373832,10.854187936587056,2.7014940383227355,214
-rdflex,cutoff and score,Linear,LGBM,0.95,0.985981308411215,12.933562651752837,2.7014940383227355,214
-rdflex,cutoff and score,Linear,Linear,0.9,0.9252336448598131,10.724343356023862,2.5881292715569817,214
-rdflex,cutoff and score,Linear,Linear,0.95,0.9766355140186916,12.77884329112302,2.5881292715569817,214
-rdflex,cutoff and score,Linear,Stacked,0.9,0.9345794392523364,10.777399597744738,2.6500175292018375,214
-rdflex,cutoff and score,Linear,Stacked,0.95,0.9719626168224299,12.842063702486124,2.6500175292018375,214
-rdflex,cutoff and score,Stacked,Global linear,0.9,0.9252336448598131,2.1786088679569744,0.4966485703629167,214
-rdflex,cutoff and score,Stacked,Global linear,0.95,0.9719626168224299,2.5959725823805626,0.4966485703629167,214
-rdflex,cutoff and score,Stacked,LGBM,0.9,0.9485981308411215,2.1461144187284016,0.4942766032999762,214
-rdflex,cutoff and score,Stacked,LGBM,0.95,0.9672897196261683,2.557253057954851,0.4942766032999762,214
-rdflex,cutoff and score,Stacked,Linear,0.9,0.9439252336448598,2.213911931815932,0.5031341173016854,214
-rdflex,cutoff and score,Stacked,Linear,0.95,0.9906542056074766,2.638038777556674,0.5031341173016854,214
-rdflex,cutoff and score,Stacked,Stacked,0.9,0.9579439252336449,2.2523882384073124,0.49263083446339334,214
-rdflex,cutoff and score,Stacked,Stacked,0.95,0.9813084112149533,2.683886124664996,0.49263083446339334,214
-rdflex,interacted cutoff and score,Global linear,Global linear,0.9,0.9439252336448598,10.533084606204715,2.536539354378303,214
-rdflex,interacted cutoff and score,Global linear,Global linear,0.95,0.9766355140186916,12.550944434208654,2.536539354378303,214
-rdflex,interacted cutoff and score,Global linear,LGBM,0.9,0.9485981308411215,10.889767355232552,2.662636398748481,214
-rdflex,interacted cutoff and score,Global linear,LGBM,0.95,0.9813084112149533,12.975958143967722,2.662636398748481,214
-rdflex,interacted cutoff and score,Global linear,Linear,0.9,0.9485981308411215,10.68507130374861,2.586187139044067,214
-rdflex,interacted cutoff and score,Global linear,Linear,0.95,0.9766355140186916,12.732047754549267,2.586187139044067,214
-rdflex,interacted cutoff and score,Global linear,Stacked,0.9,0.9439252336448598,10.558703379952977,2.603058464158783,214
-rdflex,interacted cutoff and score,Global linear,Stacked,0.95,0.9719626168224299,12.581471085973858,2.603058464158783,214
-rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.9392523364485982,2.142350464078299,0.4962040631698678,214
-rdflex,interacted cutoff and score,LGBM,Global linear,0.95,0.9813084112149533,2.5527680293585275,0.4962040631698678,214
-rdflex,interacted cutoff and score,LGBM,LGBM,0.9,0.9439252336448598,2.248059401902932,0.5371172689574487,214
-rdflex,interacted cutoff and score,LGBM,LGBM,0.95,0.9813084112149533,2.6787279978234766,0.5371172689574487,214
-rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.9299065420560748,2.2069200480948767,0.5204804556154995,214
-rdflex,interacted cutoff and score,LGBM,Linear,0.95,0.985981308411215,2.6297074342366247,0.5204804556154995,214
-rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.9439252336448598,2.1300404990101094,0.526283843809854,214
-rdflex,interacted cutoff and score,LGBM,Stacked,0.95,0.985981308411215,2.5380998012625637,0.526283843809854,214
-rdflex,interacted cutoff and score,Linear,Global linear,0.9,0.9345794392523364,10.68120559444222,2.6167228434568193,214
-rdflex,interacted cutoff and score,Linear,Global linear,0.95,0.9766355140186916,12.727441477801555,2.6167228434568193,214
-rdflex,interacted cutoff and score,Linear,LGBM,0.9,0.9485981308411215,11.082779264157297,2.7433028249989375,214
-rdflex,interacted cutoff and score,Linear,LGBM,0.95,0.9813084112149533,13.20594601880431,2.7433028249989375,214
-rdflex,interacted cutoff and score,Linear,Linear,0.9,0.9485981308411215,10.809863394765074,2.6250927449346375,214
-rdflex,interacted cutoff and score,Linear,Linear,0.95,0.9766355140186916,12.880746702552946,2.6250927449346375,214
-rdflex,interacted cutoff and score,Linear,Stacked,0.9,0.9299065420560748,10.73548376747478,2.6509536853647253,214
-rdflex,interacted cutoff and score,Linear,Stacked,0.95,0.9719626168224299,12.792117910128006,2.6509536853647253,214
-rdflex,interacted cutoff and score,Stacked,Global linear,0.9,0.9252336448598131,2.2291515095999177,0.5287095718263444,214
-rdflex,interacted cutoff and score,Stacked,Global linear,0.95,0.9719626168224299,2.6561978545145224,0.5287095718263444,214
-rdflex,interacted cutoff and score,Stacked,LGBM,0.9,0.9345794392523364,2.2108654801861354,0.5143407932379643,214
-rdflex,interacted cutoff and score,Stacked,LGBM,0.95,0.9766355140186916,2.634408706541716,0.5143407932379643,214
-rdflex,interacted cutoff and score,Stacked,Linear,0.9,0.9205607476635514,2.240692460872586,0.5126956666505772,214
-rdflex,interacted cutoff and score,Stacked,Linear,0.95,0.9672897196261683,2.6699497461546833,0.5126956666505772,214
-rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.9485981308411215,2.182225992342746,0.484470066239434,214
-rdflex,interacted cutoff and score,Stacked,Stacked,0.95,0.985981308411215,2.6002826519256894,0.484470066239434,214
-rdrobust,cutoff,linear,linear,0.9,0.9392523364485982,10.39225703260292,2.5469407480913575,214
-rdrobust,cutoff,linear,linear,0.95,0.9719626168224299,12.383138030181538,2.5469407480913575,214
+rdflex,cutoff,Global linear,Global linear,0.9,0.9444444444444444,10.550968654406873,2.5392776744200893,216
+rdflex,cutoff,Global linear,Global linear,0.95,0.9768518518518519,12.572254592024322,2.5392776744200893,216
+rdflex,cutoff,Global linear,LGBM,0.9,0.9444444444444444,10.708024190570491,2.6073374467941046,216
+rdflex,cutoff,Global linear,LGBM,0.95,0.9814814814814815,12.759397806113123,2.6073374467941046,216
+rdflex,cutoff,Global linear,Linear,0.9,0.9398148148148148,10.693313577661321,2.588240057526377,216
+rdflex,cutoff,Global linear,Linear,0.95,0.9768518518518519,12.741869029679734,2.588240057526377,216
+rdflex,cutoff,Global linear,Stacked,0.9,0.9490740740740741,10.542048532266264,2.612637626054498,216
+rdflex,cutoff,Global linear,Stacked,0.95,0.9722222222222222,12.561625610912065,2.612637626054498,216
+rdflex,cutoff,LGBM,Global linear,0.9,0.9351851851851852,2.0279514032790127,0.46622804442663607,216
+rdflex,cutoff,LGBM,Global linear,0.95,0.9675925925925926,2.41645314069128,0.46622804442663607,216
+rdflex,cutoff,LGBM,LGBM,0.9,0.9305555555555556,2.042881297411709,0.5024654331303038,216
+rdflex,cutoff,LGBM,LGBM,0.95,0.9722222222222222,2.43424320681851,0.5024654331303038,216
+rdflex,cutoff,LGBM,Linear,0.9,0.9537037037037037,2.080782411875394,0.4852661380399315,216
+rdflex,cutoff,LGBM,Linear,0.95,0.9907407407407407,2.4794051702331084,0.4852661380399315,216
+rdflex,cutoff,LGBM,Stacked,0.9,0.9074074074074074,2.0172921723310107,0.4728302559834236,216
+rdflex,cutoff,LGBM,Stacked,0.95,0.9675925925925926,2.403751883619732,0.4728302559834236,216
+rdflex,cutoff,Linear,Global linear,0.9,0.9444444444444444,10.55132710224951,2.5325716396404885,216
+rdflex,cutoff,Linear,Global linear,0.95,0.9768518518518519,12.572681708972839,2.5325716396404885,216
+rdflex,cutoff,Linear,LGBM,0.9,0.9444444444444444,10.753117458827687,2.620660533593667,216
+rdflex,cutoff,Linear,LGBM,0.95,0.9768518518518519,12.813129749357891,2.620660533593667,216
+rdflex,cutoff,Linear,Linear,0.9,0.9351851851851852,10.743662262390526,2.595884369295528,216
+rdflex,cutoff,Linear,Linear,0.95,0.9768518518518519,12.801863187896167,2.595884369295528,216
+rdflex,cutoff,Linear,Stacked,0.9,0.9444444444444444,10.401649719757378,2.4927224287383223,216
+rdflex,cutoff,Linear,Stacked,0.95,0.9768518518518519,12.394330107238822,2.4927224287383223,216
+rdflex,cutoff,Stacked,Global linear,0.9,0.9305555555555556,2.0983415675320316,0.4975883722319017,216
+rdflex,cutoff,Stacked,Global linear,0.95,0.9722222222222222,2.5003281947029072,0.4975883722319017,216
+rdflex,cutoff,Stacked,LGBM,0.9,0.9490740740740741,1.9927333689440805,0.46390758670023197,216
+rdflex,cutoff,Stacked,LGBM,0.95,0.9907407407407407,2.374488264442265,0.46390758670023197,216
+rdflex,cutoff,Stacked,Linear,0.9,0.9398148148148148,2.1047878672512663,0.4512766757906042,216
+rdflex,cutoff,Stacked,Linear,0.95,0.9814814814814815,2.5080094345872537,0.4512766757906042,216
+rdflex,cutoff,Stacked,Stacked,0.9,0.9398148148148148,2.018372202175261,0.4440441469354455,216
+rdflex,cutoff,Stacked,Stacked,0.95,0.9722222222222222,2.4050388185556275,0.4440441469354455,216
+rdflex,cutoff and score,Global linear,Global linear,0.9,0.9444444444444444,10.541731726173863,2.5466073798084476,216
+rdflex,cutoff and score,Global linear,Global linear,0.95,0.9768518518518519,12.561248113169402,2.5466073798084476,216
+rdflex,cutoff and score,Global linear,LGBM,0.9,0.9444444444444444,10.802363295011858,2.619847318234262,216
+rdflex,cutoff and score,Global linear,LGBM,0.95,0.9814814814814815,12.871809782479394,2.619847318234262,216
+rdflex,cutoff and score,Global linear,Linear,0.9,0.9444444444444444,10.716958765048908,2.583063844578886,216
+rdflex,cutoff and score,Global linear,Linear,0.95,0.9768518518518519,12.770044008248046,2.583063844578886,216
+rdflex,cutoff and score,Global linear,Stacked,0.9,0.9490740740740741,10.844485522189487,2.620657146170252,216
+rdflex,cutoff and score,Global linear,Stacked,0.95,0.9768518518518519,12.922001511922078,2.620657146170252,216
+rdflex,cutoff and score,LGBM,Global linear,0.9,0.9537037037037037,2.1504153242188013,0.4963799840481196,216
+rdflex,cutoff and score,LGBM,Global linear,0.95,0.9814814814814815,2.5623779029404297,0.4963799840481196,216
+rdflex,cutoff and score,LGBM,LGBM,0.9,0.9398148148148148,2.19952802355761,0.5288148720294119,216
+rdflex,cutoff and score,LGBM,LGBM,0.95,0.9675925925925926,2.62089929372583,0.5288148720294119,216
+rdflex,cutoff and score,LGBM,Linear,0.9,0.9444444444444444,2.194220945907011,0.47775420988075235,216
+rdflex,cutoff and score,LGBM,Linear,0.95,0.9768518518518519,2.6145755206630503,0.47775420988075235,216
+rdflex,cutoff and score,LGBM,Stacked,0.9,0.9629629629629629,2.1314900769464837,0.507224779882837,216
+rdflex,cutoff and score,LGBM,Stacked,0.95,0.9814814814814815,2.5398270799100526,0.507224779882837,216
+rdflex,cutoff and score,Linear,Global linear,0.9,0.9305555555555556,10.639058631470585,2.5797082020294453,216
+rdflex,cutoff and score,Linear,Global linear,0.95,0.9768518518518519,12.67722027384236,2.5797082020294453,216
+rdflex,cutoff and score,Linear,LGBM,0.9,0.9537037037037037,10.843507930073951,2.6816901211660595,216
+rdflex,cutoff and score,Linear,LGBM,0.95,0.9861111111111112,12.920836639068572,2.6816901211660595,216
+rdflex,cutoff and score,Linear,Linear,0.9,0.9259259259259259,10.720333460959493,2.5692901598060844,216
+rdflex,cutoff and score,Linear,Linear,0.95,0.9768518518518519,12.774065206447778,2.5692901598060844,216
+rdflex,cutoff and score,Linear,Stacked,0.9,0.9351851851851852,10.771248925216401,2.628942922146688,216
+rdflex,cutoff and score,Linear,Stacked,0.95,0.9722222222222222,12.834734724126767,2.628942922146688,216
+rdflex,cutoff and score,Stacked,Global linear,0.9,0.9259259259259259,2.1758583329529992,0.4954139177181787,216
+rdflex,cutoff and score,Stacked,Global linear,0.95,0.9722222222222222,2.5926951177735758,0.4954139177181787,216
+rdflex,cutoff and score,Stacked,LGBM,0.9,0.9490740740740741,2.14896811377524,0.49554947239669855,216
+rdflex,cutoff and score,Stacked,LGBM,0.95,0.9675925925925926,2.5606534453346264,0.49554947239669855,216
+rdflex,cutoff and score,Stacked,Linear,0.9,0.9444444444444444,2.2103831812726713,0.5009430339517977,216
+rdflex,cutoff and score,Stacked,Linear,0.95,0.9907407407407407,2.6338340119399084,0.5009430339517977,216
+rdflex,cutoff and score,Stacked,Stacked,0.9,0.9583333333333334,2.248723364922043,0.48994200235087687,216
+rdflex,cutoff and score,Stacked,Stacked,0.95,0.9814814814814815,2.6795191585585116,0.48994200235087687,216
+rdflex,interacted cutoff and score,Global linear,Global linear,0.9,0.9444444444444444,10.528753908366333,2.518597595494908,216
+rdflex,interacted cutoff and score,Global linear,Global linear,0.95,0.9768518518518519,12.545784089450876,2.518597595494908,216
+rdflex,interacted cutoff and score,Global linear,LGBM,0.9,0.9490740740740741,10.883820485971622,2.643607944035682,216
+rdflex,interacted cutoff and score,Global linear,LGBM,0.95,0.9814814814814815,12.968872012179936,2.643607944035682,216
+rdflex,interacted cutoff and score,Global linear,Linear,0.9,0.9490740740740741,10.679264733081846,2.5668725486471975,216
+rdflex,interacted cutoff and score,Global linear,Linear,0.95,0.9768518518518519,12.72512879884764,2.5668725486471975,216
+rdflex,interacted cutoff and score,Global linear,Stacked,0.9,0.9444444444444444,10.556663173569188,2.583268501046405,216
+rdflex,interacted cutoff and score,Global linear,Stacked,0.95,0.9722222222222222,12.57904003012321,2.583268501046405,216
+rdflex,interacted cutoff and score,LGBM,Global linear,0.9,0.9398148148148148,2.1382530370306743,0.4936600928743498,216
+rdflex,interacted cutoff and score,LGBM,Global linear,0.95,0.9814814814814815,2.5478856438921023,0.4936600928743498,216
+rdflex,interacted cutoff and score,LGBM,LGBM,0.9,0.9444444444444444,2.243092570442924,0.5335638194586231,216
+rdflex,interacted cutoff and score,LGBM,LGBM,0.95,0.9814814814814815,2.6728096531030787,0.5335638194586231,216
+rdflex,interacted cutoff and score,LGBM,Linear,0.9,0.9305555555555556,2.2051763510151194,0.5213516989837321,216
+rdflex,interacted cutoff and score,LGBM,Linear,0.95,0.9861111111111112,2.6276296910135963,0.5213516989837321,216
+rdflex,interacted cutoff and score,LGBM,Stacked,0.9,0.9444444444444444,2.126751117895573,0.5233380765223618,216
+rdflex,interacted cutoff and score,LGBM,Stacked,0.95,0.9861111111111112,2.5341802619125082,0.5233380765223618,216
+rdflex,interacted cutoff and score,Linear,Global linear,0.9,0.9351851851851852,10.677559557738437,2.5991484671227343,216
+rdflex,interacted cutoff and score,Linear,Global linear,0.95,0.9768518518518519,12.723096957104614,2.5991484671227343,216
+rdflex,interacted cutoff and score,Linear,LGBM,0.9,0.9490740740740741,11.089339149119295,2.725598433398943,216
+rdflex,interacted cutoff and score,Linear,LGBM,0.95,0.9814814814814815,13.213762603853324,2.725598433398943,216
+rdflex,interacted cutoff and score,Linear,Linear,0.9,0.9490740740740741,10.802881515458683,2.6051325493976867,216
+rdflex,interacted cutoff and score,Linear,Linear,0.95,0.9768518518518519,12.872427280228244,2.6051325493976867,216
+rdflex,interacted cutoff and score,Linear,Stacked,0.9,0.9305555555555556,10.739902046135317,2.632007340388683,216
+rdflex,interacted cutoff and score,Linear,Stacked,0.95,0.9722222222222222,12.797382613872113,2.632007340388683,216
+rdflex,interacted cutoff and score,Stacked,Global linear,0.9,0.9259259259259259,2.2262353572464413,0.5277443836534749,216
+rdflex,interacted cutoff and score,Stacked,Global linear,0.95,0.9722222222222222,2.6527230446636065,0.5277443836534749,216
+rdflex,interacted cutoff and score,Stacked,LGBM,0.9,0.9351851851851852,2.208657937129488,0.5111335387106734,216
+rdflex,interacted cutoff and score,Stacked,LGBM,0.95,0.9768518518518519,2.6317782567470007,0.5111335387106734,216
+rdflex,interacted cutoff and score,Stacked,Linear,0.9,0.9212962962962963,2.236992575930734,0.5108504373114083,216
+rdflex,interacted cutoff and score,Stacked,Linear,0.95,0.9675925925925926,2.6655410613245243,0.5108504373114083,216
+rdflex,interacted cutoff and score,Stacked,Stacked,0.9,0.9490740740740741,2.1809709471862324,0.48273354169573274,216
+rdflex,interacted cutoff and score,Stacked,Stacked,0.95,0.9861111111111112,2.598787173382533,0.48273354169573274,216
+rdrobust,cutoff,linear,linear,0.9,0.9398148148148148,10.388284844054892,2.528176524108971,216
+rdrobust,cutoff,linear,linear,0.95,0.9722222222222222,12.378404875591745,2.528176524108971,216
diff --git a/results/rdd/rdd_fuzzy_coverage_metadata.csv b/results/rdd/rdd_fuzzy_coverage_metadata.csv
index 3fc4f25..d3b74a5 100644
--- a/results/rdd/rdd_fuzzy_coverage_metadata.csv
+++ b/results/rdd/rdd_fuzzy_coverage_metadata.csv
@@ -1,2 +1,2 @@
 DoubleML Version,Script,Date,Total Runtime (seconds),Python Version
-0.9.dev0,rdd_fuzzy_coverage.py,2025-01-08 17:31:20,19870.016520500183,3.12.8
+0.9.dev0,rdd_fuzzy_coverage.py,2025-01-08 23:31:57,19859.63268303871,3.12.8