@stdlib/stats-base-dists-levy-entropy
v0.2.2
Published
Lévy distribution entropy.
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Entropy
Lévy distribution differential entropy.
The differential entropy (in nats) for a Lévy random variable with location μ
and scale c > 0
is
where γ
is the Euler-Mascheroni constants.
Installation
npm install @stdlib/stats-base-dists-levy-entropy
Usage
var entropy = require( '@stdlib/stats-base-dists-levy-entropy' );
entropy( mu, c )
Returns the differential entropy for a Lévy distribution with location parameter mu
and scale parameter c
(in nats).
var y = entropy( 2.0, 1.0 );
// returns ~3.324
y = entropy( 0.0, 1.0 );
// returns ~3.324
y = entropy( -1.0, 4.0 );
// returns ~4.711
If provided NaN
as any argument, the function returns NaN
.
var y = entropy( NaN, 1.0 );
// returns NaN
y = entropy( 0.0, NaN );
// returns NaN
If provided c <= 0
, the function returns NaN
.
var y = entropy( 0.0, 0.0 );
// returns NaN
y = entropy( 0.0, -1.0 );
// returns NaN
Examples
var randu = require( '@stdlib/random-base-randu' );
var entropy = require( '@stdlib/stats-base-dists-levy-entropy' );
var mu;
var c;
var y;
var i;
for ( i = 0; i < 10; i++ ) {
mu = ( randu()*10.0 ) - 5.0;
c = randu() * 20.0;
y = entropy( mu, c );
console.log( 'µ: %d, c: %d, h(X;µ,c): %d', mu.toFixed( 4 ), c.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.