Kurtosis

Half-normal distribution excess kurtosis.

The excess kurtosis of a half-normal distribution with scale sigma > 0 is

Installation

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

Usage

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

kurtosis( sigma )

Returns the excess kurtosis of a half-normal distribution with scale parameter sigma.

var x = kurtosis( 1.0 );
// returns ~0.869

var y = kurtosis( 4.0 );
// returns ~0.869

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

var x = kurtosis( 0.0 );
// returns NaN

var y = kurtosis( -1.0 );
// returns NaN

Examples

var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var kurtosis = require( '@stdlib/stats-base-dists-halfnormal-kurtosis' );

var opts = {
    'dtype': 'float64'
};
var sigma = uniform( 10, 0.0, 20.0, opts );

logEachMap( 'σ: %0.4f, Kurt(X;σ): %0.4f', sigma, kurtosis );

C APIs

Usage

#include "stdlib/stats/base/dists/halfnormal/kurtosis.h"

stdlib_base_dists_halfnormal_kurtosis( sigma )

Returns the excess kurtosis of a half-normal distribution with scale parameter sigma.

double out = stdlib_base_dists_halfnormal_kurtosis( 1.0 );
// returns ~0.869

The function accepts the following arguments:

• sigma: [in] double scale parameter.

double stdlib_base_dists_halfnormal_kurtosis( const double sigma );

Examples

#include "stdlib/stats/base/dists/halfnormal/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 sigma;
    double y;
    int i;

    for ( i = 0; i < 10; i++ ) {
        sigma = random_uniform( 0.0, 20.0 );
        y = stdlib_base_dists_halfnormal_kurtosis( sigma );
        printf( "σ: %lf, Kurt(σ): %lf\n", sigma, 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.