@stdlib/stats-base-dists-negative-binomial NPM

Negative Binomial

Negative binomial distribution.

Installation

npm install @stdlib/stats-base-dists-negative-binomial

Usage

var negativeBinomial = require( '@stdlib/stats-base-dists-negative-binomial' );

negativeBinomial

Negative binomial distribution.

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

The namespace contains the following distribution functions:

cdf( x, r, p ): negative binomial distribution cumulative distribution function.
logpmf( x, r, p ): evaluate the natural logarithm of the probability mass function (PMF) for a negative binomial distribution.
mgf( t, r, p ): negative binomial distribution moment-generating function (MGF).
pmf( x, r, p ): negative binomial distribution probability mass function (PMF).
quantile( k, r, p ): negative binomial distribution quantile function.

The namespace contains the following functions for calculating distribution properties:

kurtosis( r, p ): negative binomial distribution excess kurtosis.
mean( r, p ): negative binomial distribution expected value.
mode( r, p ): negative binomial distribution mode.
skewness( r, p ): negative binomial distribution skewness.
stdev( r, p ): negative binomial distribution standard deviation.
variance( r, p ): negative binomial distribution variance.

The namespace contains a constructor function for creating a negative binomial distribution object.

NegativeBinomial( [r, p] ): negative binomial distribution constructor.

var NegativeBinomial = require( '@stdlib/stats-base-dists-negative-binomial' ).NegativeBinomial;

var dist = new NegativeBinomial( 4.0, 0.2 );

var y = dist.pmf( 4.0 );
// returns ~0.023

Examples

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

console.log( objectKeys( negativeBinomial ) );

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.