Student's T

Student's t distribution.

Usage

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

t

Student's t distribution.

var dist = t;
// returns {...}

The namespace contains the following distribution functions:

cdf( x, v ): Student's t distribution cumulative distribution function (CDF).
logcdf( x, v ): evaluate the natural logarithm of the cumulative distribution function (CDF) for a Student's t distribution.
logpdf( x, v ): evaluate the natural logarithm of the probability density function (PDF) for a Student's t distribution.
pdf( x, v ): Student's t distribution probability density function (PDF).
quantile( p, v ): Student's t distribution quantile function.

The namespace contains the following functions for calculating distribution properties:

entropy( v ): Student's t distribution differential entropy.
kurtosis( v ): Student's t distribution excess kurtosis.
mean( v ): Student's t distribution expected value.
median( v ): Student's t distribution median.
mode( v ): Student's t distribution mode.
skewness( v ): Student's t distribution skewness.
stdev( v ): Student's t distribution variance.
variance( v ): Student's t distribution variance.

The namespace contains a constructor function for creating a Student's t distribution object.

T( [v] ): Student's t distribution constructor.

var T = require( '@stdlib/stats/base/dists/t' ).T;

var dist = new T( 2.0 );

var y = dist.cdf( 0.5 );
// returns ~0.667

Examples

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

var dof = 3;
var x = 1.5;

// Evaluate the probability density function (PDF) at a specific value:
var res = t.pdf( x, dof );
console.log( 'PDF at x = ' + x + ': ' + res );

// Evaluate the cumulative distribution function (CDF) at a specific value:
res = t.cdf( x, dof );
console.log( 'CDF at x = ' + x + ': ' + res );

// Get the mean and variance of the t distribution:
var mu = t.mean( dof );
var v = t.variance( dof );
console.log( 'Mean: ' + mu + ', Variance: ' + v );