Entropy

Binomial distribution entropy.

The entropy (in nats) for a binomial random variable is

where n is the number of trials and p is the success probability.

Installation

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

Usage

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

entropy( n, p )

Returns the entropy of a binomial distribution with number of trials n and success probability p (in nats).

var v = entropy( 20, 0.1 );
// returns ~1.667

v = entropy( 50, 0.5 );
// returns ~2.682

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

var v = entropy( NaN, 0.5 );
// returns NaN

v = entropy( 20, NaN );
// returns NaN

If provided a number of trials n which is not a nonnegative integer, the function returns NaN.

var v = entropy( 1.5, 0.5 );
// returns NaN

v = entropy( -2.0, 0.5 );
// returns NaN

If provided a success probability p outside of [0,1], the function returns NaN.

var v = entropy( 20, -1.0 );
// returns NaN

v = entropy( 20, 1.5 );
// returns NaN

Examples

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

var opts = {
    'dtype': 'float64'
};
var n = discreteUniform( 10, 0, 100, opts );
var p = uniform( 10, 0.0, 1.0, opts );

logEachMap( 'n: %0.4f, p: %0.4f, H(X;n,p): %0.4f', n, p, entropy );

C APIs

Usage

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

stdlib_base_dists_binomial_entropy( n, p )

Evaluates the entropy of a binomial distribution with n the number of trials and p the success probability.

double out = stdlib_base_dists_binomial_entropy( 20, 0.1 );
// returns ~1.667

The function accepts the following arguments:

• n: [in] int32_t number of trials.
• p: [in] double success probability.

double stdlib_base_dists_binomial_entropy( const int32_t n, const double p );

Examples

#include "stdlib/stats/base/dists/binomial/entropy.h"
#include <stdlib.h>
#include <stdio.h>
#include <stdint.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) );
}

static int32_t random_int( const int32_t min, const int32_t max ) {
    return min + (int32_t)( random_uniform( 0.0, 1.0 ) * ( max - min + 1 ) );
}

int main( void ) {
    int32_t n;
    double p;
    double v;
    int i;

    for ( i = 0; i < 25; i++ ) {
        n = random_int( 0, 100 );
        p = random_uniform( 0.0, 1.0 );
        v = stdlib_base_dists_binomial_entropy( n, p );
        printf( "n: %d, p: %lf, H(X;n,p): %lf\n", n, p, v );
    }
}

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.