@stdlib/stats-base-dists-triangular-entropy

Triangular distribution differential entropy.


Keywords
stdlib, stdmath, statistics, stats, distribution, dist, entropy, information, shannon, nats, continuous, probability, prob, triangular, univariate, javascript, node, node-js, nodejs
License
Apache-2.0
Install
npm install @stdlib/stats-base-dists-triangular-entropy@0.0.5

Documentation

Entropy

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Triangular distribution differential entropy.

The differential entropy (in nats) for a triangular random variable with lower limit a, upper limit b, and mode c is

Differential entropy for a triangular distribution.

Installation

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

Usage

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

entropy( a, b, c )

Returns the differential entropy of a triangular distribution with minimum support a, maximum supportb, and mode c (in nats).

var v = entropy( 0.0, 1.0, 0.8 );
// returns ~-0.193

v = entropy( 4.0, 12.0, 5.0 );
// returns ~1.886

v = entropy( 2.0, 8.0, 5.0 );
// returns ~1.599

If provided NaN as any argument, the function returns NaN.

var v = entropy( NaN, 4.0, 2.0 );
// returns NaN

v = entropy( 0.0, NaN, 2.0 );
// returns NaN

v = entropy( 0.0, 4.0, NaN );
// returns NaN

If provided parameters not satisfying a <= c <= b, the function returns NaN.

var y = entropy( 1.0, 0.0, 1.5 );
// returns NaN

y = entropy( 0.0, 1.0, -1.0 );
// returns NaN

y = entropy( 0.0, -1.0, 0.5 );
// returns NaN

Examples

var randu = require( '@stdlib/random-base-randu' );
var entropy = require( '@stdlib/stats-base-dists-triangular-entropy' );

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

for ( i = 0; i < 10; i++ ) {
    a = ( randu()*10.0 );
    b = ( randu()*10.0 ) + a;
    c = ( randu()*( b-a ) ) + a;
    v = entropy( a, b, c );
    console.log( 'a: %d, b: %d, c: %d, h(X;a,b,c): %d', a.toFixed( 4 ), b.toFixed( 4 ), c.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.

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License

See LICENSE.

Copyright

Copyright © 2016-2021. The Stdlib Authors.