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

    Kurtosis

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    Kumaraswamy's double bounded distribution excess kurtosis.

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

    Excess kurtosis for a Kumaraswamy's double bounded distribution.

    where 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-kurtosis

    Usage

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

    kurtosis( a, b )

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

    var v = kurtosis( 1.0, 1.0 );
    // returns ~1.8
    
    v = kurtosis( 4.0, 12.0 );
    // returns ~2.704
    
    v = kurtosis( 2.0, 8.0 );
    // returns ~2.666

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

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

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

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

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

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

    Examples

    var randu = require( '@stdlib/random-base-randu' );
    var kurtosis = require( '@stdlib/stats-base-dists-kumaraswamy-kurtosis' );
    
    var a;
    var b;
    var v;
    var i;
    
    for ( i = 0; i < 10; i++ ) {
        a = randu() * 10.0;
        b = randu() * 10.0;
        v = kurtosis( a, b );
        console.log( 'a: %d, b: %d, Kurt(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 © 2016-2022. The Stdlib Authors.

    Install

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

    Homepage

    stdlib.io

    DownloadsWeekly Downloads

    92

    Version

    0.0.7

    License

    Apache-2.0

    Unpacked Size

    47.7 kB

    Total Files

    11

    Last publish

    Collaborators

    • stdlib-bot
    • kgryte
    • planeshifter
    • rreusser