Entropy

Bradford distribution differential entropy.

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

where c is the shape parameter.

Installation

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

Usage

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

entropy( c )

Returns the differential entropy of a Bradford distribution with shape parameter c (in nats).

var v = entropy( 0.2 );
// returns ~-0.001

v = entropy( 10.0 );
// returns ~-0.229

If provided a shape parameter c <= 0, the function returns NaN.

var v = entropy( 0.0 );
// returns NaN

v = entropy( -1.5 );
// returns NaN

Examples

var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var entropy = require( '@stdlib/stats-base-dists-bradford-entropy' );

var opts = {
    'dtype': 'float64'
};
var c = uniform( 10, 0.1, 10.0, opts );

logEachMap( 'c: %0.4f, h(X;c): %0.4f', c, entropy );

C APIs

Usage

#include "stdlib/stats/base/dists/bradford/entropy.h"

stdlib_base_dists_bradford_entropy( c )

Returns the differential entropy of a Bradford distribution with shape parameter c.

double y = stdlib_base_dists_bradford_entropy( 0.5 );
// returns ~-0.007

The function accepts the following arguments:

• c: [in] double shape parameter.

double stdlib_base_dists_bradford_entropy( const double c );

Examples

#include "stdlib/stats/base/dists/bradford/entropy.h"
#include <stdlib.h>
#include <stdio.h>

static double random_uniform( const double min, const double max ) {
    double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
    return min + ( v*(max-min) );
}

int main( void ) {
    double c;
    double y;
    int i;

    for ( i = 0; i < 10; i++ ) {
        c = random_uniform( 0.01, 10.0 );
        y = stdlib_base_dists_bradford_entropy( c );
        printf( "c: %lf, h(X;c): %lf\n", c, y );
    }
}

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 © 2016-2026. The Stdlib Authors.