🚀 Socket Launch Week 🚀 Day 3: Socket Acquires Coana.Learn More
Socket
Sign inDemoInstall
Socket

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

Package Overview
Dependencies
Maintainers
0
Versions
12
Alerts
File Explorer

Advanced tools

Socket logo

Install Socket

Detect and block malicious and high-risk dependencies

Install

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

Chi-squared distribution constructor.

0.2.2
latest
Source
npm
Version published
Maintainers
0
Created
Source
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!

ChiSquare

NPM version Build Status Coverage Status

Chi-squared distribution constructor.

Installation

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

Usage

var ChiSquare = require( '@stdlib/stats-base-dists-chisquare-ctor' );

ChiSquare( [k] )

Returns an chi-squared distribution object.

var chisquare = new ChiSquare();

var mu = chisquare.mean;
// returns 1.0

By default, k = 1.0. To create a distribution having a different degrees of freedom k, provide a parameter value.

var chisquare = new ChiSquare( 4.0 );

var mu = chisquare.mean;
// returns 4.0

chisquare

A chi-squared distribution object has the following properties and methods...

Writable Properties

chisquare.k

Rate parameter of the distribution. k must be a positive number.

var chisquare = new ChiSquare( 2.0 );

var k = chisquare.k;
// returns 2.0

chisquare.k = 3.0;

k = chisquare.k;
// returns 3.0

Computed Properties

ChiSquare.prototype.entropy

Returns the differential entropy.

var chisquare = new ChiSquare( 4.0 );

var entropy = chisquare.entropy;
// returns ~2.27

ChiSquare.prototype.kurtosis

Returns the excess kurtosis.

var chisquare = new ChiSquare( 4.0 );

var kurtosis = chisquare.kurtosis;
// returns 3.0

ChiSquare.prototype.mean

Returns the expected value.

var chisquare = new ChiSquare( 4.0 );

var mu = chisquare.mean;
// returns 4.0

ChiSquare.prototype.median

Returns the median.

var chisquare = new ChiSquare( 4.0 );

var median = chisquare.median;
// returns ~3.357

ChiSquare.prototype.mode

Returns the mode.

var chisquare = new ChiSquare( 4.0 );

var mode = chisquare.mode;
// returns 2.0

ChiSquare.prototype.skewness

Returns the skewness.

var chisquare = new ChiSquare( 4.0 );

var skewness = chisquare.skewness;
// returns ~1.414

ChiSquare.prototype.stdev

Returns the standard deviation.

var chisquare = new ChiSquare( 4.0 );

var s = chisquare.stdev;
// returns ~2.828

ChiSquare.prototype.variance

Returns the variance.

var chisquare = new ChiSquare( 4.0 );

var s2 = chisquare.variance;
// returns 8.0

Methods

ChiSquare.prototype.cdf( x )

Evaluates the cumulative distribution function (CDF).

var chisquare = new ChiSquare( 2.0 );

var y = chisquare.cdf( 0.5 );
// returns ~0.221

ChiSquare.prototype.mgf( t )

Evaluates the moment-generating function (MGF).

var chisquare = new ChiSquare( 2.0 );

var y = chisquare.mgf( 0.2 );
// returns ~1.667

ChiSquare.prototype.pdf( x )

Evaluates the probability density function (PDF).

var chisquare = new ChiSquare( 2.0 );

var y = chisquare.pdf( 0.8 );
// returns ~0.335

ChiSquare.prototype.quantile( p )

Evaluates the quantile function at probability p.

var chisquare = new ChiSquare( 2.0 );

var y = chisquare.quantile( 0.5 );
// returns ~1.386

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

Examples

var ChiSquare = require( '@stdlib/stats-base-dists-chisquare-ctor' );

var chisquare = new ChiSquare( 2.0 );

var mu = chisquare.mean;
// returns 2.0

var mode = chisquare.mode;
// returns 0.0

var s2 = chisquare.variance;
// returns 4.0

var y = chisquare.cdf( 0.8 );
// returns ~0.33

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 © 2016-2024. The Stdlib Authors.

Keywords

stdlib

FAQs

Package last updated on 28 Jul 2024

Did you know?

Socket

Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.

Install

Related posts