About stdlib...
We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.
When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.
To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
Probability Density Function
Beta distribution probability density function (PDF).
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 );
y = pdf( 0.1, 1.0, 1.0 );
y = pdf( 0.8, 4.0, 2.0 );
If provided a x
outside the support [0,1]
, the function returns 0
.
var y = pdf( -0.1, 1.0, 1.0 );
y = pdf( 1.1, 1.0, 1.0 );
If provided NaN
as any argument, the function returns NaN
.
var y = pdf( NaN, 1.0, 1.0 );
y = pdf( 0.0, NaN, 1.0 );
y = pdf( 0.0, 1.0, NaN );
If provided alpha <= 0
, the function returns NaN
.
var y = pdf( 0.5, 0.0, 1.0 );
y = pdf( 0.5, -1.0, 1.0 );
If provided beta <= 0
, the function returns NaN
.
var y = pdf( 0.5, 1.0, 0.0 );
y = pdf( 0.5, 1.0, -1.0 );
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 );
y = mypdf( 0.3 );
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.
License
See LICENSE.
Copyright
Copyright © 2016-2024. The Stdlib Authors.
0.2.2 (2024-07-28)
<section class="commits">
Commits
<details>
41d41e9
- test: include trailing newlines in Julia-generated JSON fixtures (by Philipp Burckhardt)9ed7d0e
- chore: add missing trailing newlines (by Philipp Burckhardt)
</details>
</section>
<!-- /.commits -->
<section class="contributors">
Contributors
A total of 1 person contributed to this release. Thank you to this contributor:
</section>
<!-- /.contributors -->
</section>
<!-- /.release -->
<section class="release" id="v0.2.1">