@stdlib/stats-base-dists-cauchy-pdf

Cauchy distribution probability density function (PDF).


Keywords
stdlib, stdmath, statistics, stats, distribution, dist, probability, prob, pdf, continuous, univariate, cauchy, javascript, node, node-js, nodejs
License
Apache-2.0
Install
npm install @stdlib/stats-base-dists-cauchy-pdf@0.0.5

Documentation

Probability Density Function

NPM version Build Status Coverage Status dependencies

Cauchy distribution probability density function (PDF).

The probability density function (PDF) for a Cauchy random variable is

Probability density function (PDF) for a Cauchy distribution.

where x0 is the location parameter and gamma > 0 is the scale parameter.

Installation

npm install @stdlib/stats-base-dists-cauchy-pdf

Usage

var pdf = require( '@stdlib/stats-base-dists-cauchy-pdf' );

pdf( x, x0, gamma )

Evaluates the probability density function (PDF) for a Cauchy distribution with parameters x0 (location parameter) and gamma > 0 (scale parameter).

var y = pdf( 2.0, 1.0, 1.0 );
// returns ~0.159

y = pdf( 4.0, 3.0, 0.1 );
// returns ~0.0315

y = pdf( 4.0, 3.0, 3.0 );
// returns ~0.095

If provided NaN as any argument, the function returns NaN.

var y = pdf( NaN, 1.0, 1.0 );
// returns NaN

y = pdf( 2.0, NaN, 1.0 );
// returns NaN

y = pdf( 2.0, 1.0, NaN );
// returns NaN

If provided gamma <= 0, the function returns NaN.

var y = pdf( 2.0, 0.0, -1.0 );
// returns NaN

y = pdf( 2.0, 0.0, 0.0 );
// returns NaN

pdf.factory( x0, gamma )

Returns a function for evaluating the PDF of a Cauchy distribution with location parameter x0 and scale parameter gamma.

var mypdf = pdf.factory( 10.0, 2.0 );

var y = mypdf( 10.0 );
// returns ~0.159

y = mypdf( 5.0 );
// returns ~0.022

Examples

var randu = require( '@stdlib/random-base-randu' );
var EPS = require( '@stdlib/constants-float64-eps' );
var pdf = require( '@stdlib/stats-base-dists-cauchy-pdf' );

var gamma;
var x0;
var x;
var y;
var i;

for ( i = 0; i < 10; i++ ) {
    x = randu() * 10.0;
    x0 = ( randu()*10.0 ) - 5.0;
    gamma = ( randu()*20.0 ) + EPS;
    y = pdf( x, gamma, x0 );
    console.log( 'x: %d, x0: %d, γ: %d, f(x;x0,γ): %d', x.toFixed(4), x0.toFixed(4), gamma.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

Chat


License

See LICENSE.

Copyright

Copyright © 2016-2021. The Stdlib Authors.