About stdlib...
We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.
When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.
To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
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 © 2016-2024. The Stdlib Authors.