@stdlib/stats-base-dists-exponential-pdf
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Exponential distribution probability density function (PDF).
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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.
Community
License
See LICENSE.
Copyright
Copyright © 2016-2024. The Stdlib Authors.