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!
Poisson distribution constructor.
npm install @stdlib/stats-base-dists-poisson-ctor
Alternatively,
- To load the package in a website via a
script
tag without installation and bundlers, use the ES Module available on theesm
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.
var Poisson = require( '@stdlib/stats-base-dists-poisson-ctor' );
Returns an Poisson distribution object.
var poisson = new Poisson();
var lambda = poisson.mean;
// returns 1.0
By default, lambda = 1.0
. To create a distribution having a different mean parameter lambda
, provide a parameter value.
var poisson = new Poisson( 4.0 );
var lambda = poisson.mean;
// returns 4.0
A Poisson distribution object has the following properties and methods...
Mean parameter of the distribution. lambda
must be a positive number.
var poisson = new Poisson( 2.0 );
var lambda = poisson.lambda;
// returns 2.0
poisson.lambda = 3.0;
lambda = poisson.lambda;
// returns 3.0
Returns the differential entropy.
var poisson = new Poisson( 4.0 );
var entropy = poisson.entropy;
// returns ~2.087
Returns the excess kurtosis.
var poisson = new Poisson( 4.0 );
var kurtosis = poisson.kurtosis;
// returns 0.25
Returns the median.
var poisson = new Poisson( 4.0 );
var mu = poisson.mean;
// returns 4.0
Returns the median.
var poisson = new Poisson( 4.0 );
var median = poisson.median;
// returns 4.0
Returns the mode.
var poisson = new Poisson( 4.0 );
var mode = poisson.mode;
// returns 4.0
Returns the skewness.
var poisson = new Poisson( 4.0 );
var skewness = poisson.skewness;
// returns 0.5
Returns the standard deviation.
var poisson = new Poisson( 4.0 );
var s = poisson.stdev;
// returns 2.0
Returns the variance.
var poisson = new Poisson( 4.0 );
var s2 = poisson.variance;
// returns 4.0
Evaluates the cumulative distribution function (CDF).
var poisson = new Poisson( 2.0 );
var y = poisson.cdf( 0.5 );
// returns ~0.135
Evaluates the natural logarithm of the probability mass function (PMF).
var poisson = new Poisson( 2.0 );
var y = poisson.logpmf( 3.0 );
// returns ~-1.712
y = poisson.logpmf( 2.3 );
// returns -Infinity
Evaluates the moment-generating function (MGF).
var poisson = new Poisson( 2.0 );
var y = poisson.mgf( 0.5 );
// returns ~3.66
Evaluates the probability mass function (PMF).
var poisson = new Poisson( 2.0 );
var y = poisson.pmf( 3.0 );
// returns ~0.18
y = poisson.pmf( 2.3 );
// returns 0.0
Evaluates the quantile function at probability p
.
var poisson = new Poisson( 2.0 );
var y = poisson.quantile( 0.5 );
// returns 2.0
y = poisson.quantile( 1.9 );
// returns NaN
var Poisson = require( '@stdlib/stats-base-dists-poisson-ctor' );
var poisson = new Poisson( 2.0 );
var mu = poisson.mean;
// returns 2.0
var mode = poisson.mode;
// returns 2.0
var s2 = poisson.variance;
// returns 2.0
var y = poisson.cdf( 0.8 );
// returns ~0.135
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.
See LICENSE.
Copyright © 2016-2024. The Stdlib Authors.