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Rayleigh distribution differential entropy.
The differential entropy (in nats) for a Rayleigh random variable is
where σ > 0
is the scale parameter.
npm install @stdlib/stats-base-dists-rayleigh-entropy
Alternatively,
- To load the package in a website via a
script
tag without installation and bundlers, use the ES Module available on theesm
branch (see README). - If you are using Deno, visit the
deno
branch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
umd
branch (see README).
The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.
To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
var entropy = require( '@stdlib/stats-base-dists-rayleigh-entropy' );
Returns the differential entropy of a Rayleigh distribution with scale sigma
(in nats).
var y = entropy( 9.0 );
// returns ~3.139
y = entropy( 3.5 );
// returns ~2.195
If provided sigma < 0
, the function returns NaN
.
var y = entropy( -1.0 );
// returns NaN
var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var entropy = require( '@stdlib/stats-base-dists-rayleigh-entropy' );
var sigma;
var y;
var i;
for ( i = 0; i < 10; i++ ) {
sigma = randu() * 20.0;
y = entropy( sigma );
console.log( 'sigma: %d, h(X,v): %d', sigma.toFixed( 4 ), y.toFixed( 4 ) );
}
#include "stdlib/stats/base/dists/rayleigh/entropy.h"
Returns the differential entropy of a Rayleigh distribution.
double out = stdlib_base_dists_rayleigh_entropy( 9.0 );
// returns ~3.139
The function accepts the following arguments:
- sigma:
[in] double
scale parameter.
double stdlib_base_dists_rayleigh_entropy( const double sigma );
#include "stdlib/stats/base/dists/rayleigh/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 sigma;
double y;
int i;
for ( i = 0; i < 25; i++ ) {
sigma = random_uniform( 0.0, 20.0 );
y = stdlib_base_dists_rayleigh_entropy( sigma );
printf( "σ: %lf, h(σ): %lf\n", sigma, y );
}
}
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.
See LICENSE.
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