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

Kurtosis

Logistic distribution excess kurtosis.

The excess kurtosis for a logistic random variable with location μ and scale s > 0 is

Installation

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

Usage

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

kurtosis( mu, s )

Returns the excess kurtosis for a logistic distribution with location parameter mu and scale parameter s.

var y = kurtosis( 2.0, 1.0 );
// returns 1.2

y = kurtosis( 0.0, 1.0 );
// returns 1.2

y = kurtosis( -1.0, 4.0 );
// returns 1.2

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

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

y = kurtosis( 0.0, NaN );
// returns NaN

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

var y = kurtosis( 0.0, 0.0 );
// returns NaN

y = kurtosis( 0.0, -1.0 );
// returns NaN

Examples

var randu = require( '@stdlib/random-base-randu' );
var kurtosis = require( '@stdlib/stats-base-dists-logistic-kurtosis' );

var mu;
var s;
var y;
var i;

for ( i = 0; i < 10; i++ ) {
    mu = ( randu()*10.0 ) - 5.0;
    s = randu() * 20.0;
    y = kurtosis( mu, s );
    console.log( 'µ: %d, s: %d, Kurt(X;µ,s): %d', mu.toFixed( 4 ), s.toFixed( 4 ), y.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.