# @stdlib/stats-base-dists-levy-entropy

0.2.2 • Public • Published

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# Entropy

Lévy distribution differential entropy.

The differential entropy (in nats) for a Lévy random variable with location `μ` and scale `c > 0` is

where `γ` is the Euler-Mascheroni constants.

## Installation

`npm install @stdlib/stats-base-dists-levy-entropy`

## Usage

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

#### entropy( mu, c )

Returns the differential entropy for a Lévy distribution with location parameter `mu` and scale parameter `c` (in nats).

```var y = entropy( 2.0, 1.0 );
// returns ~3.324

y = entropy( 0.0, 1.0 );
// returns ~3.324

y = entropy( -1.0, 4.0 );
// returns ~4.711```

If provided `NaN` as any argument, the function returns `NaN`.

```var y = entropy( NaN, 1.0 );
// returns NaN

y = entropy( 0.0, NaN );
// returns NaN```

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

```var y = entropy( 0.0, 0.0 );
// returns NaN

y = entropy( 0.0, -1.0 );
// returns NaN```

## Examples

```var randu = require( '@stdlib/random-base-randu' );
var entropy = require( '@stdlib/stats-base-dists-levy-entropy' );

var mu;
var c;
var y;
var i;

for ( i = 0; i < 10; i++ ) {
mu = ( randu()*10.0 ) - 5.0;
c = randu() * 20.0;
y = entropy( mu, c );
console.log( 'µ: %d, c: %d, h(X;µ,c): %d', mu.toFixed( 4 ), c.toFixed( 4 ), y.toFixed( 4 ) );
}```

## 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.

## Package Sidebar

### Install

`npm i @stdlib/stats-base-dists-levy-entropy`

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