@stdlib/stats-base-dists-bernoulli NPM

Bernoulli

Bernoulli distribution.

Installation

npm install @stdlib/stats-base-dists-bernoulli

Usage

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

bernoulli

Bernoulli distribution.

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

The namespace contains the following distribution functions:

cdf( x, p ): Bernoulli distribution cumulative distribution function.
mgf( t, p ): Bernoulli distribution moment-generating function (MGF).
pmf( x, p ): Bernoulli distribution probability mass function (PMF).
quantile( r, p ): Bernoulli distribution quantile function.

The namespace contains the following functions for calculating distribution properties:

entropy( p ): Bernoulli distribution entropy.
kurtosis( p ): Bernoulli distribution excess kurtosis.
mean( p ): Bernoulli distribution expected value.
median( p ): Bernoulli distribution median.
mode( p ): Bernoulli distribution mode.
skewness( p ): Bernoulli distribution skewness.
stdev( p ): Bernoulli distribution standard deviation.
variance( p ): Bernoulli distribution variance.

The namespace contains a constructor function for creating a Bernoulli distribution object.

Bernoulli( [p] ): Bernoulli distribution constructor.

var Bernoulli = require( '@stdlib/stats-base-dists-bernoulli' ).Bernoulli;

var dist = new Bernoulli( 0.2 );

var y = dist.pmf( 0.0 );
// returns 0.8

y = dist.pmf( 1.0 );
// returns 0.2

Examples

var objectKeys = require( '@stdlib/utils-keys' );
var bernoulli = require( '@stdlib/stats-base-dists-bernoulli' );

console.log( objectKeys( bernoulli ) );

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.