@stdlib/stats-base-dists-kumaraswamy-quantile
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    Quantile Function

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    Kumaraswamy's double bounded distribution quantile function.

    The quantile function for a Kumaraswamy's double bounded random variable is

    Quantile function for a Kumaraswamy's double bounded distribution.

    for 0 <= p <= 1, where a > 0 is the first shape parameter and b > 0 is the second shape parameter.

    Installation

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

    Usage

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

    quantile( p, a, b )

    Evaluates the quantile function for a Kumaraswamy's double bounded distribution with parameters a (first shape parameter) and b (second shape parameter).

    var y = quantile( 0.5, 1.0, 1.0 );
    // returns 0.5
    
    y = quantile( 0.5, 2.0, 4.0 );
    // returns ~0.399
    
    y = quantile( 0.2, 2.0, 2.0 );
    // returns ~0.325
    
    y = quantile( 0.8, 4.0, 4.0 );
    // returns ~0.759

    If provided a probability p outside the interval [0,1], the function returns NaN.

    var y = quantile( -0.5, 4.0, 2.0 );
    // returns NaN
    
    y = quantile( 1.5, 4.0, 2.0 );
    // returns NaN

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

    var y = quantile( NaN, 1.0, 1.0 );
    // returns NaN
    
    y = quantile( 0.2, NaN, 1.0 );
    // returns NaN
    
    y = quantile( 0.2, 1.0, NaN );
    // returns NaN

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

    var y = quantile( 0.2, -1.0, 0.5 );
    // returns NaN
    
    y = quantile( 0.2, 0.0, 0.5 );
    // returns NaN

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

    var y = quantile( 0.2, 0.5, -1.0 );
    // returns NaN
    
    y = quantile( 0.2, 0.5, 0.0 );
    // returns NaN

    quantile.factory( a, b )

    Returns a function for evaluating the quantile function for a Kumaraswamy's double bounded distribution with parameters a (first shape parameter) and b (second shape parameter).

    var myQuantile = quantile.factory( 0.5, 0.5 );
    
    var y = myQuantile( 0.8 );
    // returns ~0.922
    
    y = myQuantile( 0.3 );
    // returns ~0.26

    Examples

    var randu = require( '@stdlib/random-base-randu' );
    var EPS = require( '@stdlib/constants-float64-eps' );
    var quantile = require( '@stdlib/stats-base-dists-kumaraswamy-quantile' );
    
    var a;
    var b;
    var p;
    var y;
    var i;
    
    for ( i = 0; i < 10; i++ ) {
        p = randu();
        a = ( randu()*5.0 ) + EPS;
        b = ( randu()*5.0 ) + EPS;
        y = quantile( p, a, b );
        console.log( 'p: %d, a: %d, b: %d, Q(p;a,b): %d', p.toFixed( 4 ), a.toFixed( 4 ), b.toFixed( 4 ), y.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-quantile

    Homepage

    stdlib.io

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    9

    Version

    0.0.5

    License

    Apache-2.0

    Unpacked Size

    55.2 kB

    Total Files

    11

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    Collaborators

    • stdlib-bot
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    • planeshifter
    • rreusser