@stdlib/stats-base-dists-geometric-ctor
TypeScript icon, indicating that this package has built-in type declarations

0.2.2 • Public • Published
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!

Geometric

NPM version Build Status Coverage Status

Geometric distribution constructor.

Installation

npm install @stdlib/stats-base-dists-geometric-ctor

Usage

var Geometric = require( '@stdlib/stats-base-dists-geometric-ctor' );

Geometric( [p] )

Returns a geometric distribution object.

var geometric = new Geometric();

var mean = geometric.mean;
// returns 1.0

By default, p = 0.5. To create a distribution having a different success probability p, provide a parameter value.

var geometric = new Geometric( 0.2 );

var mean = geometric.mean;
// returns 4.0

geometric

A geometric distribution object has the following properties and methods...

Writable Properties

geometric.p

Success probability of the distribution. p must be a probability.

var geometric = new Geometric( 0.2 );

var p = geometric.p;
// returns 0.2

geometric.p = 0.3;

p = geometric.p;
// returns 0.3

Computed Properties

Geometric.prototype.entropy

Returns the differential entropy.

var geometric = new Geometric( 0.4 );

var entropy = geometric.entropy;
// returns ~1.683

Geometric.prototype.kurtosis

Returns the excess kurtosis.

var geometric = new Geometric( 0.4 );

var kurtosis = geometric.kurtosis;
// returns ~6.267

Geometric.prototype.mean

Returns the median.

var geometric = new Geometric( 0.4 );

var mu = geometric.mean;
// returns ~1.5

Geometric.prototype.median

Returns the median.

var geometric = new Geometric( 0.4 );

var median = geometric.median;
// returns 1.0

Geometric.prototype.mode

Returns the mode.

var geometric = new Geometric( 0.4 );

var mode = geometric.mode;
// returns 0.0

Geometric.prototype.skewness

Returns the skewness.

var geometric = new Geometric( 0.4 );

var skewness = geometric.skewness;
// returns ~2.066

Geometric.prototype.stdev

Returns the standard deviation.

var geometric = new Geometric( 0.4 );

var s = geometric.stdev;
// returns ~1.936

Geometric.prototype.variance

Returns the variance.

var geometric = new Geometric( 0.4 );

var s2 = geometric.variance;
// returns ~3.75

Methods

Geometric.prototype.cdf( x )

Evaluates the cumulative distribution function (CDF).

var geometric = new Geometric( 0.2 );

var y = geometric.cdf( 0.5 );
// returns ~0.2

Geometric.prototype.logcdf( x )

Evaluates the natural logarithm of the cumulative distribution function (logCDF).

var geometric = new Geometric( 0.2 );

var y = geometric.logcdf( 0.5 );
// returns ~-1.609

Geometric.prototype.logpmf( x )

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

var geometric = new Geometric( 0.2 );

var y = geometric.logpmf( 3.0 );
// returns ~-2.279

y = geometric.logpmf( 2.3 );
// returns -Infinity

Geometric.prototype.mgf( t )

Evaluates the moment-generating function (MGF).

var geometric = new Geometric( 0.2 );

var y = geometric.mgf( 0.1 );
// returns ~1.908

Geometric.prototype.pmf( x )

Evaluates the probability mass function (PMF).

var geometric = new Geometric( 0.2 );

var y = geometric.pmf( 3.0 );
// returns ~0.102

y = geometric.pmf( 2.3 );
// returns 0.0

Geometric.prototype.quantile( p )

Evaluates the quantile function at probability p.

var geometric = new Geometric( 0.2 );

var y = geometric.quantile( 0.5 );
// returns 3.0

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

Examples

var Geometric = require( '@stdlib/stats-base-dists-geometric-ctor' );

var geometric = new Geometric( 0.5 );

var mu = geometric.mean;
// returns 1.0

var mode = geometric.mode;
// returns 0.0

var s2 = geometric.variance;
// returns 2.0

var y = geometric.cdf( 2.0 );
// returns 0.875

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.

Community

Chat


License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.

/@stdlib/stats-base-dists-geometric-ctor/

    Package Sidebar

    Install

    npm i @stdlib/stats-base-dists-geometric-ctor

    Homepage

    stdlib.io

    Weekly Downloads

    24

    Version

    0.2.2

    License

    Apache-2.0

    Unpacked Size

    55.6 kB

    Total Files

    11

    Last publish

    Collaborators

    • stdlib-bot
    • kgryte
    • planeshifter
    • rreusser