@stdlib/stats-base-dists-t-pdf NPM

Probability Density Function

Student's t distribution probability density function (PDF).

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

where v > 0 is the degrees of freedom.

Installation

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

Usage

var pdf = require( '@stdlib/stats-base-dists-t-pdf' );

pdf( x, v )

Evaluates the probability density function (PDF) for a Student's t distribution with degrees of freedom v.

var y = pdf( 0.3, 4.0 );
// returns ~0.355

y = pdf( 2.0, 0.7 );
// returns ~0.058

y = pdf( -1.0, 0.5 );
// returns ~0.118

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

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

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

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

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

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

pdf.factory( v )

Returns a function for evaluating the PDF of a Student's t distribution with degrees of freedom v.

var mypdf = pdf.factory( 1.0 );
var y = mypdf( 3.0 );
// returns ~0.032

y = mypdf( 1.0 );
// returns ~0.159

Examples

var randu = require( '@stdlib/random-base-randu' );
var pdf = require( '@stdlib/stats-base-dists-t-pdf' );

var v;
var x;
var y;
var i;

for ( i = 0; i < 10; i++ ) {
    x = (randu() * 6.0) - 3.0;
    v = randu() * 10.0;
    y = pdf( x, v );
    console.log( 'x: %d, v: %d, f(x;v): %d', x, v, y );
}

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.