Necessary Pigeonholing Mechanism

# npm

## @stdlib/stats-base-dists-bernoulli-kurtosis 0.0.8 • Public • Published

# Kurtosis

Bernoulli distribution excess kurtosis.

The excess kurtosis for a Bernoulli random variable is

where `p` is the success probability and `q = 1 - p`.

## Installation

`npm install @stdlib/stats-base-dists-bernoulli-kurtosis`

## Usage

`var kurtosis = require( '@stdlib/stats-base-dists-bernoulli-kurtosis' );`

#### kurtosis( p )

Returns the excess kurtosis of a Bernoulli distribution with success probability `p`.

```var v = kurtosis( 0.1 );
// returns ~5.111

v = kurtosis( 0.5 );
// returns -2.0```

If provided a success probability `p` outside of `[0,1]`, the function returns `NaN`.

```var v = kurtosis( NaN );
// returns NaN

v = kurtosis( 1.5 );
// returns NaN

v = kurtosis( -1.0 );
// returns NaN```

## Examples

```var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var kurtosis = require( '@stdlib/stats-base-dists-bernoulli-kurtosis' );

var v;
var i;
var p;

for ( i = 0; i < 10; i++ ) {
p = randu();
v = kurtosis( p );
console.log( 'p: %d, Kurt(X;p): %d', p.toFixed( 4 ), v.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.

#### Community ### Install

`npm i @stdlib/stats-base-dists-bernoulli-kurtosis`

stdlib.io

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0.0.8