Package Exports
- @stdlib/stats-base-dists-kumaraswamy-variance
This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (@stdlib/stats-base-dists-kumaraswamy-variance) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.
Readme
Variance
Kumaraswamy's double bounded distribution variance.
The variance for a Kumaraswamy's double bounded random variable with first shape parameter a and second shape parameter b is
where the raw moments of the distribution are given by
with B denoting the beta function.
Installation
npm install @stdlib/stats-base-dists-kumaraswamy-varianceUsage
var variance = require( '@stdlib/stats-base-dists-kumaraswamy-variance' );variance( a, b )
Returns the variance of a Kumaraswamy's double bounded distribution with first shape parameter a and second shape parameter b.
var v = variance( 1.0, 1.0 );
// returns ~0.083
v = variance( 4.0, 12.0 );
// returns ~0.017
v = variance( 2.0, 8.0 );
// returns ~0.021If provided NaN as any argument, the function returns NaN.
var v = variance( NaN, 2.0 );
// returns NaN
v = variance( 2.0, NaN );
// returns NaNIf provided a <= 0, the function returns NaN.
var y = variance( -1.0, 0.5 );
// returns NaN
y = variance( 0.0, 0.5 );
// returns NaNIf provided b <= 0, the function returns NaN.
var y = variance( 0.5, -1.0 );
// returns NaN
y = variance( 0.5, 0.0 );
// returns NaNExamples
var randu = require( '@stdlib/random-base-randu' );
var variance = require( '@stdlib/stats-base-dists-kumaraswamy-variance' );
var a;
var b;
var v;
var i;
for ( i = 0; i < 10; i++ ) {
a = randu() * 10.0;
b = randu() * 10.0;
v = variance( a, b );
console.log( 'a: %d, b: %d, Var(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 © 2016-2021. The Stdlib Authors.