@stdlib/stats-base-dists-arcsine-entropy
v0.2.2
Published
Arcsine distribution differential entropy.
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Entropy
Arcsine distribution differential entropy.
The differential entropy (in nats) for an arcsine random variable with minimum support a
and maximum support b
is
Installation
npm install @stdlib/stats-base-dists-arcsine-entropy
Usage
var entropy = require( '@stdlib/stats-base-dists-arcsine-entropy' );
entropy( a, b )
Returns the differential entropy of an arcsine distribution with minimum support a
and maximum support b
(in nats).
var v = entropy( 0.0, 1.0 );
// returns ~-0.242
v = entropy( 4.0, 12.0 );
// returns ~1.838
v = entropy( 2.0, 8.0 );
// returns ~1.55
If provided NaN
as any argument, the function returns NaN
.
var v = entropy( NaN, 2.0 );
// returns NaN
v = entropy( 2.0, NaN );
// returns NaN
If provided a >= b
, the function returns NaN
.
var y = entropy( 3.0, 2.0 );
// returns NaN
y = entropy( 3.0, 3.0 );
// returns NaN
Examples
var randu = require( '@stdlib/random-base-randu' );
var EPS = require( '@stdlib/constants-float64-eps' );
var entropy = require( '@stdlib/stats-base-dists-arcsine-entropy' );
var a;
var b;
var v;
var i;
for ( i = 0; i < 10; i++ ) {
a = ( randu()*10.0 );
b = ( randu()*10.0 ) + a + EPS;
v = entropy( a, b );
console.log( 'a: %d, b: %d, h(X;a,b): %d', a.toFixed( 4 ), b.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.
Community
License
See LICENSE.
Copyright
Copyright © 2016-2024. The Stdlib Authors.