@stdlib/stats-base-dists-kumaraswamy-skewness
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    Skewness

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    Kumaraswamy's double bounded distribution skewness.

    The skewness for a Kumaraswamy's double bounded random variable with first shape parameter a and second shape parameter b is

    Skewness for a Kumaraswamy's double bounded distribution.

    where σ^2 is the variance and the raw moments of the distribution are given by

    Raw moments for a Kumaraswamy's double bounded distribution.

    with B denoting the beta function.

    Installation

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

    Usage

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

    skewness( a, b )

    Returns the skewness of a Kumaraswamy's double bounded distribution with first shape parameter a and second shape parameter b.

    var v = skewness( 1.0, 1.0 );
    // returns ~0.0
    
    v = skewness( 4.0, 12.0 );
    // returns ~-0.201
    
    v = skewness( 2.0, 8.0 );
    // returns ~0.384

    If provided NaN as any argument, the function returns NaN.

    var v = skewness( NaN, 2.0 );
    // returns NaN
    
    v = skewness( 2.0, NaN );
    // returns NaN

    If provided a <= 0, the function returns NaN.

    var y = skewness( -1.0, 0.5 );
    // returns NaN
    
    y = skewness( 0.0, 0.5 );
    // returns NaN

    If provided b <= 0, the function returns NaN.

    var y = skewness( 0.5, -1.0 );
    // returns NaN
    
    y = skewness( 0.5, 0.0 );
    // returns NaN

    Examples

    var randu = require( '@stdlib/random-base-randu' );
    var skewness = require( '@stdlib/stats-base-dists-kumaraswamy-skewness' );
    
    var a;
    var b;
    var v;
    var i;
    
    for ( i = 0; i < 10; i++ ) {
        a = randu() * 10.0;
        b = randu() * 10.0;
        v = skewness( a, b );
        console.log( 'a: %d, b: %d, skew(X;a,b): %d', a.toFixed( 4 ), b.toFixed( 4 ), v.toFixed( 4 ) );
    }

    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 © 2016-2021. The Stdlib Authors.

    Install

    npm i @stdlib/stats-base-dists-kumaraswamy-skewness

    Homepage

    stdlib.io

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    8

    Version

    0.0.5

    License

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    11

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    Collaborators

    • stdlib-bot
    • kgryte
    • planeshifter
    • rreusser