# @stdlib/stats-base-dists-exponential-pdf

0.2.1 • Public • Published

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# Probability Density Function

Exponential distribution probability density function (PDF).

The probability density function (PDF) for an exponential random variable is

where `λ` is the rate parameter.

## Installation

`npm install @stdlib/stats-base-dists-exponential-pdf`

## Usage

`var pdf = require( '@stdlib/stats-base-dists-exponential-pdf' );`

#### pdf( x, lambda )

Evaluates the probability density function (PDF) for an exponential distribution with rate parameter `lambda`.

```var y = pdf( 2.0, 0.3 );
// returns ~0.165

y = pdf( 2.0, 1.0 );
// returns ~0.135```

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

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

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

If provided `lambda < 0`, the function returns `NaN`.

```var y = pdf( 2.0, -1.0 );
// returns NaN```

#### pdf.factory( lambda )

Partially apply `lambda` to create a reusable `function` for evaluating the PDF.

```var mypdf = pdf.factory( 0.1 );

var y = mypdf( 8.0 );
// returns ~0.045

y = mypdf( 5.0 );
// returns ~0.06```

## Examples

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

var lambda;
var x;
var y;
var i;

for ( i = 0; i < 10; i++ ) {
x = randu() * 10.0;
lambda = randu() * 10.0;
y = pdf( x, lambda );
console.log( 'x: %d, λ: %d, f(x;λ): %d', x, lambda, y );
}```

## 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-exponential-pdf`

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