@stdlib/stats-base-dists-rayleigh-ctor
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    0.0.7 • Public • Published

    Rayleigh

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    Rayleigh distribution constructor.

    Installation

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

    Usage

    var Rayleigh = require( '@stdlib/stats-base-dists-rayleigh-ctor' );

    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

    var Rayleigh = require( '@stdlib/stats-base-dists-rayleigh-ctor' );
    
    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

    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 © 2016-2022. The Stdlib Authors.

    Install

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

    Homepage

    stdlib.io

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    Version

    0.0.7

    License

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