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Beta distributed pseudorandom numbers.
npm install @stdlib/random-base-betaAlternatively,
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var beta = require( '@stdlib/random-base-beta' );Returns a pseudorandom number drawn from a beta distribution with parameters alpha (first shape parameter) and beta (second shape parameter).
var r = beta( 2.0, 5.0 );
// returns <number>If alpha <= 0 or beta <= 0, the function returns NaN.
var r = beta( 2.0, -2.0 );
// returns NaN
r = beta( -2.0, 2.0 );
// returns NaNIf alpha or beta is NaN, the function returns NaN.
var r = beta( NaN, 5.0 );
// returns NaN
r = beta( 2.0, NaN );
// returns NaNReturns a pseudorandom number generator (PRNG) for generating pseudorandom numbers drawn from a beta distribution.
var rand = beta.factory();
var r = rand( 1.5, 1.5 );
// returns <number>If provided alpha and beta, the returned generator returns random variates from the specified distribution.
// Draw from beta( 1.5, 1.5 ) distribution:
var rand = beta.factory( 1.5, 1.5 );
var r = rand();
// returns <number>
r = rand();
// returns <number>If not provided alpha and beta, the returned generator requires that both parameters be provided at each invocation.
var rand = beta.factory();
var r = rand( 1.0, 1.0 );
// returns <number>
r = rand( 3.14, 2.25 );
// returns <number>The function accepts the following options:
- prng: pseudorandom number generator for generating uniformly distributed pseudorandom numbers on the interval
[0,1). If provided, the function ignores both thestateandseedoptions. In order to seed the returned pseudorandom number generator, one must seed the providedprng(assuming the providedprngis seedable). - seed: pseudorandom number generator seed.
- state: a
Uint32Arraycontaining pseudorandom number generator state. If provided, the function ignores theseedoption. - copy:
booleanindicating whether to copy a provided pseudorandom number generator state. Setting this option tofalseallows sharing state between two or more pseudorandom number generators. Setting this option totrueensures that a returned generator has exclusive control over its internal state. Default:true.
To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the prng option.
var minstd = require( '@stdlib/random-base-minstd' );
var rand = beta.factory({
'prng': minstd.normalized
});
var r = rand( 2.0, 4.0 );
// returns <number>To seed a pseudorandom number generator, set the seed option.
var rand1 = beta.factory({
'seed': 12345
});
var r1 = rand1( 2.0, 3.0 );
// returns <number>
var rand2 = beta.factory( 2.0, 3.0, {
'seed': 12345
});
var r2 = rand2();
// returns <number>
var bool = ( r1 === r2 );
// returns trueTo return a generator having a specific initial state, set the generator state option.
var rand;
var bool;
var r;
var i;
// Generate pseudorandom numbers, thus progressing the generator state:
for ( i = 0; i < 1000; i++ ) {
r = beta( 2.0, 4.0 );
}
// Create a new PRNG initialized to the current state of `beta`:
rand = beta.factory({
'state': beta.state
});
// Test that the generated pseudorandom numbers are the same:
bool = ( rand( 2.0, 4.0 ) === beta( 2.0, 4.0 ) );
// returns trueThe generator name.
var str = beta.NAME;
// returns 'beta'The underlying pseudorandom number generator.
var prng = beta.PRNG;
// returns <Function>The value used to seed beta().
var rand;
var r;
var i;
// Generate pseudorandom values...
for ( i = 0; i < 100; i++ ) {
r = beta( 2.0, 2.0 );
}
// Generate the same pseudorandom values...
rand = beta.factory( 2.0, 2.0, {
'seed': beta.seed
});
for ( i = 0; i < 100; i++ ) {
r = rand();
}If provided a PRNG for uniformly distributed numbers, this value is null.
var rand = beta.factory({
'prng': Math.random
});
var seed = rand.seed;
// returns nullLength of generator seed.
var len = beta.seedLength;
// returns <number>If provided a PRNG for uniformly distributed numbers, this value is null.
var rand = beta.factory({
'prng': Math.random
});
var len = rand.seedLength;
// returns nullWritable property for getting and setting the generator state.
var r = beta( 2.0, 5.0 );
// returns <number>
r = beta( 2.0, 5.0 );
// returns <number>
// ...
// Get a copy of the current state:
var state = beta.state;
// returns <Uint32Array>
r = beta( 2.0, 5.0 );
// returns <number>
r = beta( 2.0, 5.0 );
// returns <number>
// Reset the state:
beta.state = state;
// Replay the last two pseudorandom numbers:
r = beta( 2.0, 5.0 );
// returns <number>
r = beta( 2.0, 5.0 );
// returns <number>
// ...If provided a PRNG for uniformly distributed numbers, this value is null.
var rand = beta.factory({
'prng': Math.random
});
var state = rand.state;
// returns nullLength of generator state.
var len = beta.stateLength;
// returns <number>If provided a PRNG for uniformly distributed numbers, this value is null.
var rand = beta.factory({
'prng': Math.random
});
var len = rand.stateLength;
// returns nullSize (in bytes) of generator state.
var sz = beta.byteLength;
// returns <number>If provided a PRNG for uniformly distributed numbers, this value is null.
var rand = beta.factory({
'prng': Math.random
});
var sz = rand.byteLength;
// returns nullSerializes the pseudorandom number generator as a JSON object.
var o = beta.toJSON();
// returns { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }If provided a PRNG for uniformly distributed numbers, this method returns null.
var rand = beta.factory({
'prng': Math.random
});
var o = rand.toJSON();
// returns null- If PRNG state is "shared" (meaning a state array was provided during PRNG creation and not copied) and one sets the generator state to a state array having a different length, the PRNG does not update the existing shared state and, instead, points to the newly provided state array. In order to synchronize PRNG output according to the new shared state array, the state array for each relevant PRNG must be explicitly set.
- If PRNG state is "shared" and one sets the generator state to a state array of the same length, the PRNG state is updated (along with the state of all other PRNGs sharing the PRNG's state array).
var beta = require( '@stdlib/random-base-beta' );
var seed;
var rand;
var i;
// Generate pseudorandom numbers...
for ( i = 0; i < 100; i++ ) {
console.log( beta( 2.0, 2.0 ) );
}
// Create a new pseudorandom number generator...
seed = 1234;
rand = beta.factory( 6.0, 2.0, {
'seed': seed
});
for ( i = 0; i < 100; i++ ) {
console.log( rand() );
}
// Create another pseudorandom number generator using a previous seed...
rand = beta.factory( 2.0, 2.0, {
'seed': beta.seed
});
for ( i = 0; i < 100; i++ ) {
console.log( rand() );
}- Ahrens, J.H., and U. Dieter. 1974. "Computer methods for sampling from gamma, beta, poisson and bionomial distributions." Computing 12 (3): 223–46. doi:10.1007/BF02293108.
- Jöhnk, M.D. 1964. "Erzeugung von Betaverteilten Und Gammaverteilten Zufallszahlen." Metrika 8: 5–15. <http://eudml.org/doc/175224>.
@stdlib/random-array/beta: create an array containing pseudorandom numbers drawn from a beta distribution.@stdlib/random-iter/beta: create an iterator for generating pseudorandom numbers drawn from a beta distribution.@stdlib/random-streams/beta: create a readable stream for generating pseudorandom numbers drawn from a beta distribution.
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