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The variance for a Weibull random variable is
where λ > 0 is the shape parameter, k > 0 is the scale parameter, and Γ denotes the gamma function.
npm install @stdlib/stats-base-dists-weibull-variancevar variance = require( '@stdlib/stats-base-dists-weibull-variance' );Returns the variance of a Weibull distribution with parameters k (shape parameter) and lambda (scale parameter).
var v = variance( 1.0, 1.0 );
// returns 1.0
v = variance( 4.0, 12.0 );
// returns ~9.311
v = variance( 8.0, 2.0 );
// returns ~0.078If 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 k <= 0, the function returns NaN.
var v = variance( 0.0, 1.0 );
// returns NaN
v = variance( -1.0, 1.0 );
// returns NaNIf provided lambda <= 0, the function returns NaN.
var v = variance( 1.0, 0.0 );
// returns NaN
v = variance( 1.0, -1.0 );
// returns NaNvar randu = require( '@stdlib/random-base-randu' );
var EPS = require( '@stdlib/constants-float64-eps' );
var variance = require( '@stdlib/stats-base-dists-weibull-variance' );
var lambda;
var k;
var v;
var i;
for ( i = 0; i < 10; i++ ) {
k = ( randu()*10.0 ) + EPS;
lambda = ( randu()*10.0 ) + EPS;
v = variance( k, lambda );
console.log( 'k: %d, λ: %d, Var(X;k,λ): %d', k.toFixed( 4 ), lambda.toFixed( 4 ), v.toFixed( 4 ) );
}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.
See LICENSE.
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