@stdlib/stats-base-dists-weibull-kurtosis NPM

Kurtosis

Weibull distribution excess kurtosis.

The excess kurtosis for a Weibull random variable with shape parameter λ > 0 and scale parameter k > 0 is

where Γ_i = Γ( 1 + i / k ).

Installation

npm install @stdlib/stats-base-dists-weibull-kurtosis

Usage

var kurtosis = require( '@stdlib/stats-base-dists-weibull-kurtosis' );

kurtosis( k, lambda )

Returns the excess kurtosis of a Weibull distribution with shape parameter k and scale parameter lambda.

var v = kurtosis( 1.0, 1.0 );
// returns 6.0

v = kurtosis( 4.0, 12.0 );
// returns ~-0.252

v = kurtosis( 8.0, 2.0 );
// returns ~0.328

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

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

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

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

var v = kurtosis( 0.0, 1.0 );
// returns NaN

v = kurtosis( -1.0, 1.0 );
// returns NaN

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

var v = kurtosis( 1.0, 0.0 );
// returns NaN

v = kurtosis( 1.0, -1.0 );
// returns NaN

Examples

var randu = require( '@stdlib/random-base-randu' );
var EPS = require( '@stdlib/constants-float64-eps' );
var kurtosis = require( '@stdlib/stats-base-dists-weibull-kurtosis' );

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 = kurtosis( k, lambda );
    console.log( 'k: %d, λ: %d, Kurt(X;k,λ): %d', k.toFixed( 4 ), lambda.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.