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

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

Negative binomial distribution constructor.

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About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

Negative Binomial

NPM version Build Status Coverage Status

Negative binomial distribution constructor.

Installation

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

Usage

var NegativeBinomial = require( '@stdlib/stats-base-dists-negative-binomial-ctor' );
NegativeBinomial( [r, p] )

Returns a negative binomial distribution object.

var nbinomial = new NegativeBinomial();

var mu = nbinomial.mean;
// returns 1.0

By default, r = 1.0 and p = 0.5. To create a distribution having a different r (number of trials until experiment is stopped) and p (success probability), provide the corresponding arguments.

var nbinomial = new NegativeBinomial( 4.0, 0.2 );

var mu = nbinomial.mean;
// returns 16.0

nbinomial

A negative binomial distribution object has the following properties and methods...

Writable Properties

nbinomial.r

Number of trials of the distribution. r must be a positive number.

var nbinomial = new NegativeBinomial();

var r = nbinomial.r;
// returns 1.0

nbinomial.r = 4.5;

r = nbinomial.r;
// returns 4.5
nbinomial.p

Success probability of the distribution. p must be a number between 0 and 1.

var nbinomial = new NegativeBinomial( 4.0, 0.2 );

var p = nbinomial.p;
// returns 0.2

nbinomial.p = 0.7;

p = nbinomial.p;
// returns 0.7

Computed Properties

NegativeBinomial.prototype.kurtosis

Returns the excess kurtosis.

var nbinomial = new NegativeBinomial( 12.0, 0.4 );

var kurtosis = nbinomial.kurtosis;
// returns ~0.522
NegativeBinomial.prototype.mean

Returns the expected value.

var nbinomial = new NegativeBinomial( 12.0, 0.4 );

var mu = nbinomial.mean;
// returns ~18.0
NegativeBinomial.prototype.mode

Returns the mode.

var nbinomial = new NegativeBinomial( 12.0, 0.4 );

var mode = nbinomial.mode;
// returns 16.0
NegativeBinomial.prototype.skewness

Returns the skewness.

var nbinomial = new NegativeBinomial( 12.0, 0.4 );

var skewness = nbinomial.skewness;
// returns ~0.596
NegativeBinomial.prototype.stdev

Returns the standard deviation.

var nbinomial = new NegativeBinomial( 12.0, 0.4 );

var s = nbinomial.stdev;
// returns ~6.708
NegativeBinomial.prototype.variance

Returns the variance.

var nbinomial = new NegativeBinomial( 12.0, 0.4 );

var s2 = nbinomial.variance;
// returns ~45.0

Methods

NegativeBinomial.prototype.cdf( x )

Evaluates the cumulative distribution function (CDF).

var nbinomial = new NegativeBinomial( 4.0, 0.2 );

var y = nbinomial.cdf( 3.5 );
// returns ~0.033
NegativeBinomial.prototype.logpmf( x )

Evaluates the natural logarithm of the probability mass function (PMF).

var nbinomial = new NegativeBinomial( 4.0, 0.2 );

var y = nbinomial.logpmf( 4.0 );
// returns ~-3.775
NegativeBinomial.prototype.mgf( t )

Evaluates the moment-generating function (MGF).

var nbinomial = new NegativeBinomial( 4.0, 0.2 );

var y = nbinomial.mgf( 0.1 );
// returns ~1.66
NegativeBinomial.prototype.pmf( x )

Evaluates the probability mass function (PMF).

var nbinomial = new NegativeBinomial( 4.0, 0.2 );

var y = nbinomial.pmf( 4.0 );
// returns ~0.023
NegativeBinomial.prototype.quantile( p )

Evaluates the quantile function at probability p.

var nbinomial = new NegativeBinomial( 4.0, 0.2 );

var y = nbinomial.quantile( 0.5 );
// returns 15.0

y = nbinomial.quantile( 1.9 );
// returns NaN

Examples

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

var nbinomial = new NegativeBinomial( 10.0, 0.4 );

var mu = nbinomial.mean;
// returns 15.0

var mode = nbinomial.mode;
// returns 13.0

var s2 = nbinomial.variance;
// returns ~37.5

var y = nbinomial.cdf( 8.0 );
// returns ~0.135

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.

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License

See LICENSE.

Copyright © 2016-2024. The Stdlib Authors.

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Package last updated on 24 Feb 2024

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