Package Exports
- @stdlib/stats-base-dists-beta-kurtosis
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Readme
Kurtosis
Beta distribution excess kurtosis.
The excess kurtosis for a beta random variable is
where α > 0
is the first shape parameter and β > 0
is the second shape parameter.
Installation
npm install @stdlib/stats-base-dists-beta-kurtosis
Usage
var kurtosis = require( '@stdlib/stats-base-dists-beta-kurtosis' );
kurtosis( alpha, beta )
Returns the excess kurtosis of a beta distribution with parameters alpha
(first shape parameter) and beta
(second shape parameter).
var v = kurtosis( 1.0, 1.0 );
// returns -1.2
v = kurtosis( 4.0, 12.0 );
// returns ~0.082
v = kurtosis( 8.0, 2.0 );
// returns ~0.490
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 alpha <= 0
, the function returns NaN
.
var v = kurtosis( 0.0, 1.0 );
// returns NaN
v = kurtosis( -1.0, 1.0 );
// returns NaN
If provided beta <= 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-beta-kurtosis' );
var alpha;
var beta;
var v;
var i;
for ( i = 0; i < 10; i++ ) {
alpha = ( randu()*10.0 ) + EPS;
beta = ( randu()*10.0 ) + EPS;
v = kurtosis( alpha, beta );
console.log( 'α: %d, β: %d, Kurt(X;α,β): %d', alpha.toFixed( 4 ), beta.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.
License
See LICENSE.
Copyright
Copyright © 2016-2021. The Stdlib Authors.