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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!

Rayleigh

NPM version Build Status Coverage Status

Rayleigh distribution constructor.

Usage

To use in Observable,

Rayleigh = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-rayleigh-ctor@umd/browser.js' )

To vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:

var Rayleigh = require( 'path/to/vendor/umd/stats-base-dists-rayleigh-ctor/index.js' )

To include the bundle in a webpage,

<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-rayleigh-ctor@umd/browser.js"></script>

If no recognized module system is present, access bundle contents via the global scope:

<script type="text/javascript">
(function () {
    window.Rayleigh;
})();
</script>

Rayleigh( [sigma] )

Returns an Rayleigh distribution object.

var rayleigh = new Rayleigh();

var mu = rayleigh.mean;
// returns ~1.253

By default, sigma = 1.0. To create a distribution having a different scale parameter sigma, provide a parameter value.

var rayleigh = new Rayleigh( 4.0 );

var mu = rayleigh.mean;
// returns ~5.013

rayleigh

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

Writable Properties

rayleigh.sigma

Scale parameter of the distribution. sigma must be a positive number.

var rayleigh = new Rayleigh( 2.0 );

var sigma = rayleigh.sigma;
// returns 2.0

rayleigh.sigma = 3.0;

sigma = rayleigh.sigma;
// returns 3.0

Computed Properties

Rayleigh.prototype.entropy

Returns the differential entropy.

var rayleigh = new Rayleigh( 4.0 );

var entropy = rayleigh.entropy;
// returns ~2.328

Rayleigh.prototype.kurtosis

Returns the excess kurtosis.

var rayleigh = new Rayleigh( 4.0 );

var kurtosis = rayleigh.kurtosis;
// returns ~0.245

Rayleigh.prototype.mean

Returns the median.

var rayleigh = new Rayleigh( 4.0 );

var mu = rayleigh.mean;
// returns ~5.013

Rayleigh.prototype.median

Returns the median.

var rayleigh = new Rayleigh( 4.0 );

var median = rayleigh.median;
// returns ~4.71

Rayleigh.prototype.mode

Returns the mode.

var rayleigh = new Rayleigh( 4.0 );

var mode = rayleigh.mode;
// returns 4.0

Rayleigh.prototype.skewness

Returns the skewness.

var rayleigh = new Rayleigh( 4.0 );

var skewness = rayleigh.skewness;
// returns ~0.631

Rayleigh.prototype.stdev

Returns the standard deviation.

var rayleigh = new Rayleigh( 4.0 );

var s = rayleigh.stdev;
// returns ~2.62

Rayleigh.prototype.variance

Returns the variance.

var rayleigh = new Rayleigh( 4.0 );

var s2 = rayleigh.variance;
// returns ~6.867

Methods

Rayleigh.prototype.cdf( x )

Evaluates the cumulative distribution function (CDF).

var rayleigh = new Rayleigh( 2.0 );

var y = rayleigh.cdf( 1.5 );
// returns ~0.245

Rayleigh.prototype.logcdf( x )

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

var rayleigh = new Rayleigh( 2.0 );

var y = rayleigh.logcdf( 1.5 );
// returns ~-1.406

Rayleigh.prototype.logpdf( x )

Evaluates the natural logarithm of the probability density function (PDF).

var rayleigh = new Rayleigh( 2.0 );

var y = rayleigh.logpdf( 0.8 );
// returns ~-1.689

Rayleigh.prototype.mgf( t )

Evaluates the moment-generating function (MGF).

var rayleigh = new Rayleigh( 2.0 );

var y = rayleigh.mgf( 0.5 );
// returns ~5.586

Rayleigh.prototype.pdf( x )

Evaluates the probability density function (PDF).

var rayleigh = new Rayleigh( 2.0 );

var y = rayleigh.pdf( 0.8 );
// returns ~0.185

Rayleigh.prototype.quantile( p )

Evaluates the quantile function at probability p.

var rayleigh = new Rayleigh( 2.0 );

var y = rayleigh.quantile( 0.5 );
// returns ~2.355

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

Examples

<!DOCTYPE html>
<html lang="en">
<body>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-rayleigh-ctor@umd/browser.js"></script>
<script type="text/javascript">
(function () {

var rayleigh = new Rayleigh( 2.0, 4.0 );

var mu = rayleigh.mean;
// returns ~2.507

var mode = rayleigh.mode;
// returns 2.0

var s2 = rayleigh.variance;
// returns ~1.717

var y = rayleigh.cdf( 0.8 );
// returns ~0.077

})();
</script>
</body>
</html>

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

Copyright © 2016-2024. The Stdlib Authors.