@stdlib/stats-base-dists-weibull-kurtosis
v0.3.1
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Weibull distribution excess kurtosis.
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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-kurtosisUsage
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 ~0.328If provided NaN as any argument, the function returns NaN.
var v = kurtosis( NaN, 2.0 );
// returns NaN
v = kurtosis( 2.0, NaN );
// returns NaNIf provided k <= 0, the function returns NaN.
var v = kurtosis( 0.0, 1.0 );
// returns NaN
v = kurtosis( -1.0, 1.0 );
// returns NaNIf provided lambda <= 0, the function returns NaN.
var v = kurtosis( 1.0, 0.0 );
// returns NaN
v = kurtosis( 1.0, -1.0 );
// returns NaNExamples
var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var EPS = require( '@stdlib/constants-float64-eps' );
var kurtosis = require( '@stdlib/stats-base-dists-weibull-kurtosis' );
var opts = {
'dtype': 'float64'
};
var lambda = uniform( 10, EPS, 10.0, opts );
var k = uniform( 10, EPS, 10.0, opts );
logEachMap( 'k: %0.4f, λ: %0.4f, Kurt(X;k,λ): %0.4f', k, lambda, kurtosis );C APIs
Usage
#include "stdlib/stats/base/dists/weibull/kurtosis.h"stdlib_base_dists_weibull_kurtosis( k, lambda )
Returns the excess kurtosis of a Weibull distribution with shape parameter k and scale parameter lambda.
double out = stdlib_base_dists_weibull_kurtosis( 4.0, 12.0 );
// returns ~-0.252The function accepts the following arguments:
- k:
[in] doubleshape parameter. - lambda:
[in] doublescale parameter.
double stdlib_base_dists_weibull_kurtosis( const double k, const double lambda );Examples
#include "stdlib/stats/base/dists/weibull/kurtosis.h"
#include <stdlib.h>
#include <stdio.h>
static double random_uniform( const double min, const double max ) {
double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
return min + ( v*(max-min) );
}
int main( void ) {
double lambda;
double k;
double y;
int i;
for ( i = 0; i < 25; i++ ) {
k = random_uniform( 0.0, 10.0 );
lambda = random_uniform( 0.0, 10.0 );
y = stdlib_base_dists_weibull_kurtosis( k, lambda );
printf( "k: %lf, λ: %lf, Kurt(X;k,λ): %lf\n", k, lambda, y );
}
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 © 2016-2026. The Stdlib Authors.
