npm package: @stdlib/stats-base-dists-logistic-entropy
Description: Logistic distribution entropy.
Author: The Stdlib Authors
Latest version: 0.3.1

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# Entropy

[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url] <!-- [![dependencies][dependencies-image]][dependencies-url] -->

> [Logistic][logistic-distribution] distribution [differential entropy][entropy].

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<section class="intro">

The [differential entropy][entropy] (in [nats][nats]) for a [logistic][logistic-distribution] random variable with location `μ` and scale `s > 0` is

<!-- <equation class="equation" label="eq:logistic_entropy" align="center" raw="h\left( X \right) = \ln( s ) + 2s" alt="Differential entropy for a logistic distribution."> -->

<div class="equation" align="center" data-raw-text="h\left( X \right) = \ln( s ) + 2s" data-equation="eq:logistic_entropy">
    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@51534079fef45e990850102147e8945fb023d1d0/lib/node_modules/@stdlib/stats/base/dists/logistic/entropy/docs/img/equation_logistic_entropy.svg" alt="Differential entropy for a logistic distribution.">
    <br>
</div>

<!-- </equation> -->

</section>

<!-- /.intro -->

<!-- Package usage documentation. -->

<section class="installation">

## Installation

```bash
npm install @stdlib/stats-base-dists-logistic-entropy
```

</section>

<section class="usage">

## 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
```

</section>

<!-- /.usage -->

<!-- Package usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="notes">

</section>

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<!-- Package usage examples. -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```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 );
```

</section>

<!-- /.examples -->

<!-- C interface documentation. -->

* * *

<section class="c">

## C APIs

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<section class="intro">

</section>

<!-- /.intro -->

<!-- C usage documentation. -->

<section class="usage">

### Usage

```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.
-   **s**: `[in] double` scale parameter.

```c
double stdlib_base_dists_logistic_entropy( const double mu, const double s );
```

</section>

<!-- /.usage -->

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<section class="notes">

</section>

<!-- /.notes -->

<!-- C API usage examples. -->

<section class="examples">

### Examples

```c
#include "stdlib/stats/base/dists/logistic/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 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 );
    }
}
```

</section>

<!-- /.examples -->

</section>

<!-- /.c -->

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</section>

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</section>

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* * *

## 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

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---

## License

See [LICENSE][stdlib-license].


## Copyright

Copyright &copy; 2016-2026. The Stdlib [Authors][stdlib-authors].

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[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

</section>

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