@stdlib/stats-base-dists-logistic-kurtosis
v0.3.1
Published
Logistic distribution kurtosis.
Readme
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-kurtosisUsage
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 1.2If provided NaN as any argument, the function returns NaN.
var y = kurtosis( NaN, 1.0 );
// returns NaN
y = kurtosis( 0.0, NaN );
// returns NaNIf provided s <= 0, the function returns NaN.
var y = kurtosis( 0.0, 0.0 );
// returns NaN
y = kurtosis( 0.0, -1.0 );
// returns NaNExamples
var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var kurtosis = require( '@stdlib/stats-base-dists-logistic-kurtosis' );
var opts = {
'dtype': 'float64'
};
var mu = uniform( 10, -5.0, 5.0, opts );
var s = uniform( 10, 0.0, 20.0, opts );
logEachMap( 'µ: %0.4f, s: %0.4f, Kurt(X;µ,s): %0.4f', mu, s, kurtosis );C APIs
Usage
#include "stdlib/stats/base/dists/logistic/kurtosis.h"stdlib_base_dists_logistic_kurtosis( mu, s )
Returns the excess kurtosis for a logistic distribution with location mu and scale s.
double out = stdlib_base_dists_logistic_kurtosis( 0.0, 1.0 );
// returns 1.2The function accepts the following arguments:
- mu:
[in] doublelocation parameter. - s:
[in] doublescale parameter.
double stdlib_base_dists_logistic_kurtosis( const double mu, const double s );Examples
#include "stdlib/stats/base/dists/logistic/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 mu;
double s;
double y;
int i;
for ( i = 0; i < 25; i++ ) {
mu = random_uniform( -5.0, 5.0 );
s = random_uniform( 0.0, 20.0 );
y = stdlib_base_dists_logistic_kurtosis( mu, s );
printf( "µ: %lf, s: %lf, Kurt(X;µ,s): %lf\n", mu, s, 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.
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License
See LICENSE.
Copyright
Copyright © 2016-2026. The Stdlib Authors.
