@stdlib/stats-base-dists-cauchy-entropy
v0.3.1
Published
Cauchy distribution differential entropy.
Readme
Entropy
Cauchy distribution differential entropy.
The differential entropy for a Cauchy random variable with location parameter x0 and scale parameter Ɣ > 0 is
Installation
npm install @stdlib/stats-base-dists-cauchy-entropyUsage
var entropy = require( '@stdlib/stats-base-dists-cauchy-entropy' );entropy( x0, gamma )
Returns the differential entropy of a Cauchy distribution with location parameter x0 and scale parameter gamma (in nats).
var v = entropy( 10.0, 5.0 );
// returns ~4.14
v = entropy( 7.0, 2.0 );
// returns ~3.224If provided NaN as any argument, the function returns NaN.
var v = entropy( NaN, 5.0 );
// returns NaN
v = entropy( 20.0, NaN );
// returns NaNIf provided gamma <= 0, the function returns NaN.
var v = entropy( 1.0, -1.0 );
// returns NaN
v = entropy( 1.0, 0.0 );
// returns NaNExamples
var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var EPS = require( '@stdlib/constants-float64-eps' );
var entropy = require( '@stdlib/stats-base-dists-cauchy-entropy' );
var opts = {
'dtype': 'float64'
};
var gamma = uniform( 10, EPS, 10.0, opts );
var x0 = uniform( 10, 0.0, 100.0, opts );
logEachMap( 'x0: %0.4f, γ: %0.4f, h(X;x0,γ): %0.4f', x0, gamma, entropy );C APIs
Usage
#include "stdlib/stats/base/dists/cauchy/entropy.h"stdlib_base_dists_cauchy_entropy( x0, gamma )
Evaluates the differential entropy of a Cauchy distribution with location parameter x0 and scale parameter gamma (in nats).
double out = stdlib_base_dists_cauchy_entropy( 10.0, 5.0 );
// returns ~4.14The function accepts the following arguments:
- x0:
[in] doublelocation parameter. - gamma:
[in] doublescale parameter.
double stdlib_base_dists_cauchy_entropy( const double x0, const double gamma );Examples
#include "stdlib/stats/base/dists/cauchy/entropy.h"
#include "stdlib/constants/float64/eps.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 gamma;
double x0;
double y;
int i;
for ( i = 0; i < 25; i++ ) {
x0 = random_uniform( 0.0, 100.0 );
gamma = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 );
y = stdlib_base_dists_cauchy_entropy( x0, gamma );
printf( "x0: %lf, γ: %lf, h(X;x0,γ): %lf\n", x0, gamma, 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.
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License
See LICENSE.
Copyright
Copyright © 2016-2026. The Stdlib Authors.
