@stdlib/stats-base-dists-invgamma-entropy
v0.3.1
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Inverse gamma distribution differential entropy.
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Entropy
Inverse gamma distribution differential entropy.
The differential entropy (in nats) for an inverse gamma random variable is
where α > 0 is the shape parameter, β > 0 is the rate parameter, Γ and denotes the gamma and Ψ the digamma function.
Installation
npm install @stdlib/stats-base-dists-invgamma-entropyUsage
var entropy = require( '@stdlib/stats-base-dists-invgamma-entropy' );entropy( alpha, beta )
Returns the differential entropy of an inverse gamma distribution with shape parameter alpha and rate parameter beta (in nats).
var v = entropy( 1.0, 1.0 );
// returns ~2.154
v = entropy( 4.0, 12.0 );
// returns ~1.996
v = entropy( 8.0, 2.0 );
// returns ~-0.922If provided NaN as any argument, the function returns NaN.
var v = entropy( NaN, 2.0 );
// returns NaN
v = entropy( 2.0, NaN );
// returns NaNIf provided alpha <= 0, the function returns NaN.
var v = entropy( 0.0, 1.0 );
// returns NaN
v = entropy( -1.0, 1.0 );
// returns NaNIf provided beta <= 0, the function returns NaN.
var v = entropy( 1.0, 0.0 );
// returns NaN
v = entropy( 1.0, -1.0 );
// returns NaNExamples
var EPS = require( '@stdlib/constants-float64-eps' );
var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var entropy = require( '@stdlib/stats-base-dists-invgamma-entropy' );
var opts = {
'dtype': 'float64'
};
var alpha = uniform( 10, EPS, 10.0, opts );
var beta = uniform( 10, EPS, 10.0, opts );
logEachMap( 'α: %0.4f, β: %0.4f, h(X;α,β): %0.4f', alpha, beta, entropy );C APIs
Usage
#include "stdlib/stats/base/dists/invgamma/entropy.h"stdlib_base_dists_invgamma_entropy( alpha, beta )
Returns the differential entropy of an inverse gamma distribution.
double out = stdlib_base_dists_invgamma_entropy( 1.0, 1.0 );
// returns ~2.154The function accepts the following arguments:
- alpha:
[in] doubleshape parameter. - beta:
[in] doublerate parameter.
double stdlib_base_dists_invgamma_entropy( const double alpha, const double beta );Examples
#include "stdlib/stats/base/dists/invgamma/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 alpha;
double beta;
double y;
int i;
for ( i = 0; i < 25; i++ ) {
alpha = random_uniform( 0, 20 );
beta = random_uniform( 0, 20 );
y = stdlib_base_dists_invgamma_entropy( alpha, beta );
printf( "α: %lf, β: %lf, h(X;α,β): %lf\n", alpha, beta, 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.
