@stdlib/stats-base-dists-cosine-kurtosis
v0.2.2
Published
Raised cosine distribution kurtosis.
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Kurtosis
Raised cosine distribution excess kurtosis.
The excess kurtosis for a raised cosine random variable with location parameter mu
and scale parameter s
is
Installation
npm install @stdlib/stats-base-dists-cosine-kurtosis
Usage
var kurtosis = require( '@stdlib/stats-base-dists-cosine-kurtosis' );
kurtosis( mu, s )
Returns the excess kurtosis for a raised cosine distribution with location parameter mu
and scale parameter s
.
var y = kurtosis( 2.0, 1.0 );
// returns ~-0.594
y = kurtosis( 0.0, 1.0 );
// returns ~-0.594
y = kurtosis( -1.0, 4.0 );
// returns ~-0.594
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-cosine-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.
Community
License
See LICENSE.
Copyright
Copyright © 2016-2024. The Stdlib Authors.