@stdlib/stats-base-dists-logistic-entropy
v0.3.1TypeScript
Logistic distribution entropy.
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Published by The Stdlib Authors
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Entropy
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> [Logistic][logistic-distribution] distribution [differential entropy][entropy].
The [differential entropy][entropy] (in [nats][nats]) for a [logistic][logistic-distribution] random variable with location μ and scale s > 0 is
Installation
``bash`
npm install @stdlib/stats-base-dists-logistic-entropy
Usage
`javascript`
var entropy = require( '@stdlib/stats-base-dists-logistic-entropy' );
#### entropy( mu, s )
Returns the [differential entropy][entropy] for a [logistic][logistic-distribution] distribution with location parameter mu and scale parameter s (in [nats][nats]).
`javascript
var y = entropy( 2.0, 1.0 );
// returns 2.0
y = entropy( 0.0, 1.0 );
// returns 2.0
y = entropy( -1.0, 4.0 );
// returns ~3.386
`
If provided NaN as any argument, the function returns NaN.
`javascript
var y = entropy( NaN, 1.0 );
// returns NaN
y = entropy( 0.0, NaN );
// returns NaN
`
If provided s <= 0, the function returns NaN.
`javascript
var y = entropy( 0.0, 0.0 );
// returns NaN
y = entropy( 0.0, -1.0 );
// returns NaN
`
Examples
`javascript
var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var entropy = require( '@stdlib/stats-base-dists-logistic-entropy' );
var opts = {
'dtype': 'float64'
};
var mu = uniform( 10, -5.0, 5.0, opts );
var s = uniform( 10, 0.0, 20.0, opts );
logEachMap( 'µ: %0.4f, s: %0.4f, h(X;µ,s): %0.4f', mu, s, entropy );
`
*
C APIs
$3
`c`
#include "stdlib/stats/base/dists/logistic/entropy.h"
#### stdlib_base_dists_logistic_entropy( mu, s )
Returns the differential entropy for a logistic distribution with location mu and scale s.
`c`
double out = stdlib_base_dists_logistic_entropy( 0.0, 1.0 );
// returns 2.0
The function accepts the following arguments:
- mu: [in] double location parameter.[in] double
- s: scale parameter.
`c`
double stdlib_base_dists_logistic_entropy( const double mu, const double s );
$3
`c
#include "stdlib/stats/base/dists/logistic/entropy.h"
#include
#include
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 mu;
double s;
double y;
int i;
for ( i = 0; i < 25; i++ ) {
mu = random_uniform( -5.0, 5.0 );
s = random_uniform( 0.0, 20.0 );
y = stdlib_base_dists_logistic_entropy( mu, s );
printf( "µ: %lf, s: %lf, h(X;µ,s): %lf\n", mu, s, y );
}
}
`
*
Notice
This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib].
#### Community
[![Chat][chat-image]][chat-url]
---
License
See [LICENSE][stdlib-license].
Copyright
Copyright © 2016-2026. The Stdlib [Authors][stdlib-authors].
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[umd]: https://github.com/umdjs/umd
[es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules
[deno-url]: https://github.com/stdlib-js/stats-base-dists-logistic-entropy/tree/deno
[deno-readme]: https://github.com/stdlib-js/stats-base-dists-logistic-entropy/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/stats-base-dists-logistic-entropy/tree/umd
[umd-readme]: https://github.com/stdlib-js/stats-base-dists-logistic-entropy/blob/umd/README.md
[esm-url]: https://github.com/stdlib-js/stats-base-dists-logistic-entropy/tree/esm
[esm-readme]: https://github.com/stdlib-js/stats-base-dists-logistic-entropy/blob/esm/README.md
[branches-url]: https://github.com/stdlib-js/stats-base-dists-logistic-entropy/blob/main/branches.md
[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-base-dists-logistic-entropy/main/LICENSE
[logistic-distribution]: https://en.wikipedia.org/wiki/Logistic_distribution
[entropy]: https://en.wikipedia.org/wiki/Entropy_%28information_theory%29
[nats]: https://en.wikipedia.org/wiki/Nat_%28unit%29