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

    Kumaraswamy

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    Kumaraswamy's double bounded distribution constructor.

    Installation

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

    Usage

    var Kumaraswamy = require( '@stdlib/stats-base-dists-kumaraswamy-ctor' );

    Kumaraswamy( [a, b] )

    Returns a Kumaraswamy's double bounded distribution object.

    var kumaraswamy = new Kumaraswamy();
    
    var mu = kumaraswamy.mean;
    // returns 0.5

    By default, a = 1.0 and b = 1.0. To create a distribution having a different a (first shape parameter) and b (second shape parameter), provide the corresponding arguments.

    var kumaraswamy = new Kumaraswamy( 2.0, 4.0 );
    
    var mu = kumaraswamy.mean;
    // returns ~0.406

    kumaraswamy

    A Kumaraswamy's double bounded distribution object has the following properties and methods...

    Writable Properties

    kumaraswamy.a

    First shape parameter of the distribution. a must be a positive number.

    var kumaraswamy = new Kumaraswamy();
    
    var a = kumaraswamy.a;
    // returns 1.0
    
    kumaraswamy.a = 3.0;
    
    a = kumaraswamy.a;
    // returns 3.0

    kumaraswamy.b

    Second shape parameter of the distribution. b must be a positive number.

    var kumaraswamy = new Kumaraswamy( 2.0, 4.0 );
    
    var b = kumaraswamy.b;
    // returns 4.0
    
    kumaraswamy.b = 3.0;
    
    b = kumaraswamy.b;
    // returns 3.0

    Computed Properties

    Kumaraswamy.prototype.kurtosis

    Returns the excess kurtosis.

    var kumaraswamy = new Kumaraswamy( 4.0, 12.0 );
    
    var kurtosis = kumaraswamy.kurtosis;
    // returns ~2.704

    Kumaraswamy.prototype.mean

    Returns the expected value.

    var kumaraswamy = new Kumaraswamy( 4.0, 12.0 );
    
    var mu = kumaraswamy.mean;
    // returns ~0.481

    Kumaraswamy.prototype.mode

    Returns the mode.

    var kumaraswamy = new Kumaraswamy( 4.0, 12.0 );
    
    var mode = kumaraswamy.mode;
    // returns ~0.503

    Kumaraswamy.prototype.skewness

    Returns the skewness.

    var kumaraswamy = new Kumaraswamy( 4.0, 12.0 );
    
    var skewness = kumaraswamy.skewness;
    // returns ~-0.201

    Kumaraswamy.prototype.stdev

    Returns the standard deviation.

    var kumaraswamy = new Kumaraswamy( 4.0, 12.0 );
    
    var s = kumaraswamy.stdev;
    // returns ~0.13

    Kumaraswamy.prototype.variance

    Returns the variance.

    var kumaraswamy = new Kumaraswamy( 4.0, 12.0 );
    
    var s2 = kumaraswamy.variance;
    // returns ~0.017

    Methods

    Kumaraswamy.prototype.cdf( x )

    Evaluates the cumulative distribution function (CDF).

    var kumaraswamy = new Kumaraswamy( 2.0, 4.0 );
    
    var y = kumaraswamy.cdf( 0.5 );
    // returns ~0.684

    Kumaraswamy.prototype.logcdf( x )

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

    var kumaraswamy = new Kumaraswamy( 2.0, 4.0 );
    
    var y = kumaraswamy.logcdf( 0.5 );
    // returns ~-0.38

    Kumaraswamy.prototype.logpdf( x )

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

    var kumaraswamy = new Kumaraswamy( 2.0, 4.0 );
    
    var y = kumaraswamy.logpdf( 0.8 );
    // returns ~-1.209

    Kumaraswamy.prototype.pdf( x )

    Evaluates the probability density function (PDF).

    var kumaraswamy = new Kumaraswamy( 2.0, 4.0 );
    
    var y = kumaraswamy.pdf( 0.8 );
    // returns ~0.299

    Kumaraswamy.prototype.quantile( p )

    Evaluates the quantile function at probability p.

    var kumaraswamy = new Kumaraswamy( 2.0, 4.0 );
    
    var y = kumaraswamy.quantile( 0.5 );
    // returns ~0.399
    
    y = kumaraswamy.quantile( 1.9 );
    // returns NaN

    Examples

    var Kumaraswamy = require( '@stdlib/stats-base-dists-kumaraswamy-ctor' );
    
    var kumaraswamy = new Kumaraswamy( 2.0, 4.0 );
    
    var mu = kumaraswamy.mean;
    // returns ~0.406
    
    var mode = kumaraswamy.mode;
    // returns ~0.378
    
    var s2 = kumaraswamy.variance;
    // returns ~0.035
    
    var y = kumaraswamy.cdf( 0.8 );
    // returns ~0.983

    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-kumaraswamy-ctor

    Homepage

    stdlib.io

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    Version

    0.0.7

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    • stdlib-bot
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