@stdlib/stats-base-dists-beta-pdf
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Beta distribution probability density function (PDF).
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Probability Density Function
Beta distribution probability density function (PDF).
The probability density function (PDF) for a beta random variable is
where alpha > 0
is the first shape parameter and beta > 0
is the second shape parameter.
Installation
npm install @stdlib/stats-base-dists-beta-pdf
Usage
var pdf = require( '@stdlib/stats-base-dists-beta-pdf' );
pdf( x, alpha, beta )
Evaluates the probability density function (PDF) for a beta distribution with parameters alpha
(first shape parameter) and beta
(second shape parameter).
var y = pdf( 0.5, 0.5, 1.0 );
// returns ~0.707
y = pdf( 0.1, 1.0, 1.0 );
// returns 1.0
y = pdf( 0.8, 4.0, 2.0 );
// returns ~2.048
If provided a x
outside the support [0,1]
, the function returns 0
.
var y = pdf( -0.1, 1.0, 1.0 );
// returns 0.0
y = pdf( 1.1, 1.0, 1.0 );
// returns 0.0
If provided NaN
as any argument, the function returns NaN
.
var y = pdf( NaN, 1.0, 1.0 );
// returns NaN
y = pdf( 0.0, NaN, 1.0 );
// returns NaN
y = pdf( 0.0, 1.0, NaN );
// returns NaN
If provided alpha <= 0
, the function returns NaN
.
var y = pdf( 0.5, 0.0, 1.0 );
// returns NaN
y = pdf( 0.5, -1.0, 1.0 );
// returns NaN
If provided beta <= 0
, the function returns NaN
.
var y = pdf( 0.5, 1.0, 0.0 );
// returns NaN
y = pdf( 0.5, 1.0, -1.0 );
// returns NaN
pdf.factory( alpha, beta )
Returns a function
for evaluating the PDF for a beta distribution with parameters alpha
(first shape parameter) and beta
(second shape parameter).
var mypdf = pdf.factory( 0.5, 0.5 );
var y = mypdf( 0.8 );
// returns ~0.796
y = mypdf( 0.3 );
// returns ~0.695
Examples
var randu = require( '@stdlib/random-base-randu' );
var EPS = require( '@stdlib/constants-float64-eps' );
var pdf = require( '@stdlib/stats-base-dists-beta-pdf' );
var alpha;
var beta;
var x;
var y;
var i;
for ( i = 0; i < 10; i++ ) {
x = randu();
alpha = ( randu()*5.0 ) + EPS;
beta = ( randu()*5.0 ) + EPS;
y = pdf( x, alpha, beta );
console.log( 'x: %d, α: %d, β: %d, f(x;α,β): %d', x.toFixed( 4 ), alpha.toFixed( 4 ), beta.toFixed( 4 ), y.toFixed( 4 ) );
}
Notice
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
Community
License
See LICENSE.
Copyright
Copyright © 2016-2024. The Stdlib Authors.