@stdlib/stats-base-dists-exponential-ctor

About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

Exponential

Exponential distribution constructor.

Installation

npm install @stdlib/stats-base-dists-exponential-ctor

Usage

var Exponential = require( '@stdlib/stats-base-dists-exponential-ctor' );

Exponential( [lambda] )

Returns an exponential distribution object.

var exponential = new Exponential();

var mu = exponential.mean;
// returns 1.0

By default, lambda = 1.0. To create a distribution having a different rate parameter lambda, provide a parameter value.

var exponential = new Exponential( 4.0 );

var mu = exponential.mean;
// returns 0.25

---

exponential

An exponential distribution object has the following properties and methods...

Writable Properties

exponential.lambda

Rate parameter of the distribution. lambda must be a positive number.

var exponential = new Exponential( 2.0 );

var lambda = exponential.lambda;
// returns 2.0

exponential.lambda = 3.0;

lambda = exponential.lambda;
// returns 3.0

---

Computed Properties

Exponential.prototype.entropy

Returns the differential entropy.

var exponential = new Exponential( 4.0 );

var entropy = exponential.entropy;
// returns ~-0.386

Exponential.prototype.kurtosis

Returns the excess kurtosis.

var exponential = new Exponential( 4.0 );

var kurtosis = exponential.kurtosis;
// returns 6.0

Exponential.prototype.mean

Returns the expected value.

var exponential = new Exponential( 4.0 );

var mu = exponential.mean;
// returns 0.25

Exponential.prototype.median

Returns the median.

var exponential = new Exponential( 4.0 );

var median = exponential.median;
// returns ~0.173

Exponential.prototype.mode

Returns the mode.

var exponential = new Exponential( 4.0 );

var mode = exponential.mode;
// returns 0.0

Exponential.prototype.skewness

Returns the skewness.

var exponential = new Exponential( 4.0 );

var skewness = exponential.skewness;
// returns 2.0

Exponential.prototype.stdev

Returns the standard deviation.

var exponential = new Exponential( 4.0 );

var s = exponential.stdev;
// returns 0.25

Exponential.prototype.variance

Returns the variance.

var exponential = new Exponential( 4.0 );

var s2 = exponential.variance;
// returns ~0.063

---

Methods

Exponential.prototype.cdf( x )

Evaluates the cumulative distribution function (CDF).

var exponential = new Exponential( 2.0 );

var y = exponential.cdf( 0.5 );
// returns ~0.632

Exponential.prototype.logcdf( x )

Evaluates the natural logarithm of the cumulative distribution function (CDF).

var exponential = new Exponential( 2.0 );

var y = exponential.logcdf( 0.5 );
// returns ~-0.459

Exponential.prototype.logpdf( x )

Evaluates the natural logarithm of the probability density function (PDF).

var exponential = new Exponential( 2.0 );

var y = exponential.logpdf( 0.8 );
// returns ~-0.907

Exponential.prototype.mgf( t )

Evaluates the moment-generating function (MGF).

var exponential = new Exponential( 2.0 );

var y = exponential.mgf( 0.5 );
// returns ~1.333

Exponential.prototype.pdf( x )

Evaluates the probability density function (PDF).

var exponential = new Exponential( 2.0 );

var y = exponential.pdf( 0.8 );
// returns ~0.404

Exponential.prototype.quantile( p )

Evaluates the quantile function at probability p.

var exponential = new Exponential( 2.0 );

var y = exponential.quantile( 0.5 );
// returns ~0.347

y = exponential.quantile( 1.9 );
// returns NaN

---

Examples

var Exponential = require( '@stdlib/stats-base-dists-exponential-ctor' );

var exponential = new Exponential( 2.0 );

var mu = exponential.mean;
// returns 0.5

var mode = exponential.mode;
// returns 0.0

var s2 = exponential.variance;
// returns 0.25

var y = exponential.cdf( 0.8 );
// returns ~0.798

---

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.