Median

Kumaraswamy's double bounded distribution median.

The median for a Kumaraswamy's double bounded random variable is

where a is the first shape parameter and b the second shape parameter.

Installation

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

Usage

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

median( a, b )

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

var v = median( 1.0, 1.0 );
// returns 0.5

v = median( 4.0, 12.0 );
// returns ~0.487

v = median( 2.0, 8.0 );
// returns ~0.288

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

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

v = median( 2.0, NaN );
// returns NaN

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

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

y = median( 0.0, 0.5 );
// returns NaN

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

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

y = median( 0.5, 0.0 );
// returns NaN

Examples

var randu = require( '@stdlib/random-base-randu' );
var median = require( '@stdlib/stats-base-dists-kumaraswamy-median' );

var a;
var b;
var v;
var i;

for ( i = 0; i < 10; i++ ) {
    a = randu() * 10.0;
    b = randu() * 10.0;
    v = median( a, b );
    console.log( 'a: %d, b: %d, Median(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.

Community

License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.