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Exponential

Exponential distribution constructor.

Installation

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

Alternatively,

• To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
• If you are using Deno, visit the deno branch (see README for usage intructions).
• For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

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

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License

See LICENSE.

Copyright

Copyright © 2016-2026. The Stdlib Authors.