npm package: @stdlib/stats-base-dists-bradford-entropy
Description: Bradford distribution differential entropy.
Author: The Stdlib Authors
Latest version: 0.1.1

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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] -->

> [Bradford][bradford-distribution] distribution [differential entropy][entropy].

<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->

<section class="intro">

The [differential entropy][entropy] (in [nats][nats]) for a [Bradford][bradford-distribution] random variable is

<!-- <equation class="equation" label="eq:bradford_entropy" align="center" raw="h\left( X \right) = \frac{1}{2}\ln(1+c) - \ln\left(\frac{c}{\ln(1+c)}\right)" alt="Differential entropy for a Bradford distribution."> -->

<div class="equation" align="center" data-raw-text="h\left( X \right) = \frac{1}{2}\ln(1+c) - \ln\left(\frac{c}{\ln(1+c)}\right)" data-equation="eq:bradford_entropy">
    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@591cf9d5c3a0cd3c1ceec961e5c49d73a68374cb/lib/node_modules/@stdlib/stats/base/dists/bradford/entropy/docs/img/equation_bradford_entropy.svg" alt="Differential entropy for a Bradford distribution.">
    <br>
</div>

<!-- </equation> -->

where `c` is the shape parameter.

</section>

<!-- /.intro -->

<!-- Package usage documentation. -->

<section class="installation">

## Installation

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

</section>

<section class="usage">

## Usage

```javascript
var entropy = require( '@stdlib/stats-base-dists-bradford-entropy' );
```

#### entropy( c )

Returns the [differential entropy][entropy] of a [Bradford][bradford-distribution] distribution with shape parameter `c` (in [nats][nats]).

```javascript
var v = entropy( 0.2 );
// returns ~-0.001

v = entropy( 10.0 );
// returns ~-0.229
```

If provided a shape parameter `c <= 0`, the function returns `NaN`.

```javascript
var v = entropy( 0.0 );
// returns NaN

v = entropy( -1.5 );
// 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>

<!-- /.notes -->

<!-- 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-bradford-entropy' );

var opts = {
    'dtype': 'float64'
};
var c = uniform( 10, 0.1, 10.0, opts );

logEachMap( 'c: %0.4f, h(X;c): %0.4f', c, entropy );
```

</section>

<!-- /.examples -->

<!-- C interface documentation. -->

* * *

<section class="c">

## C APIs

<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->

<section class="intro">

</section>

<!-- /.intro -->

<!-- C usage documentation. -->

<section class="usage">

### Usage

```c
#include "stdlib/stats/base/dists/bradford/entropy.h"
```

#### stdlib_base_dists_bradford_entropy( c )

Returns the differential entropy of a Bradford distribution with shape parameter `c`.

```c
double y = stdlib_base_dists_bradford_entropy( 0.5 );
// returns ~-0.007
```

The function accepts the following arguments:

-   **c**: `[in] double` shape parameter.

```c
double stdlib_base_dists_bradford_entropy( const double c );
```

</section>

<!-- /.usage -->

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

<section class="notes">

</section>

<!-- /.notes -->

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

<section class="examples">

### Examples

```c
#include "stdlib/stats/base/dists/bradford/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 c;
    double y;
    int i;

    for ( i = 0; i < 10; i++ ) {
        c = random_uniform( 0.01, 10.0 );
        y = stdlib_base_dists_bradford_entropy( c );
        printf( "c: %lf, h(X;c): %lf\n", c, y );
    }
}
```

</section>

<!-- /.examples -->

</section>

<!-- /.c -->

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<section class="related">

</section>

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<section class="main-repo" >

* * *

## 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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[bradford-distribution]: https://en.wikipedia.org/wiki/Bradford%27s_law

[entropy]: https://en.wikipedia.org/wiki/Entropy_%28information_theory%29

[nats]: https://en.wikipedia.org/wiki/Nat_%28unit%29

</section>

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