@stdlib/stats-base-dists-uniform-entropy NPM

Entropy

Uniform distribution differential entropy.

The differential entropy (in nats) for a uniform random variable is

where a is the minimum support and b is the maximum support. The parameters must satisfy a < b.

Installation

npm install @stdlib/stats-base-dists-uniform-entropy

Usage

var entropy = require( '@stdlib/stats-base-dists-uniform-entropy' );

entropy( a, b )

Returns the differential entropy of a uniform distribution with minimum support a and maximum support b (in nats).

var v = entropy( 0.0, 1.0 );
// returns 0.0

v = entropy( 4.0, 12.0 );
// returns ~2.079

v = entropy( 2.0, 8.0 );
// returns ~1.792

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 entropy = require( '@stdlib/stats-base-dists-uniform-entropy' );

var a;
var b;
var v;
var i;

for ( i = 0; i < 10; i++ ) {
    a = ( randu()*10.0 );
    b = ( randu()*10.0 ) + a;
    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.