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

upper V a r left-parenthesis upper X right-parenthesis equals m 2 minus m 1 squared

where the raw moments of the distribution are given by

m Subscript n Baseline equals b upper B left-parenthesis 1 plus StartFraction n Over a EndFraction comma b right-parenthesis

with B denoting the beta function.

Usage

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 ~0.021

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

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

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

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

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

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

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

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

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

Examples

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 ) );
}
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