@stdlib/random-base-poisson

Poisson distributed random numbers.

https://github.com/stdlib-js/random-base-poisson

Science Score: 57.0%

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Keywords

counts generator javascript math mathematics node node-js nodejs poisrand poisson prng pseudorandom rand randn random rng rpois statistics stats stdlib

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Repository

Poisson distributed random numbers.

Basic Info

Host: GitHub
Owner: stdlib-js
License: apache-2.0
Language: JavaScript
Default Branch: main
Homepage: https://github.com/stdlib-js/stdlib
Size: 2.41 MB

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counts generator javascript math mathematics node node-js nodejs poisrand poisson prng pseudorandom rand randn random rng rpois statistics stats stdlib

Created over 4 years ago · Last pushed 7 months ago

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Readme Changelog Contributing License Code of conduct Citation Security

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 Random Numbers

Poisson distributed pseudorandom numbers.

## Installation ```bash npm install @stdlib/random-base-poisson ``` Alternatively, - To load the package in a website via a `script` tag without installation and bundlers, use the [ES Module][es-module] available on the [`esm`][esm-url] branch (see [README][esm-readme]). - If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions). - For use in Observable, or in browser/node environments, use the [Universal Module Definition (UMD)][umd] build available on the [`umd`][umd-url] branch (see [README][umd-readme]). The [branches.md][branches-url] 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 ```javascript var poisson = require( '@stdlib/random-base-poisson' ); ``` #### poisson( lambda ) Returns a pseudorandom number drawn from a [Poisson][poisson] distribution with mean parameter `lambda`. ```javascript var r = poisson( 7.9 ); // returns ``` If `lambda <= 0` or `lambda` is `NaN`, the function returns `NaN`. ```javascript var r = poisson( -2.0 ); // returns NaN r = poisson( NaN ); // returns NaN ``` #### poisson.factory( \[lambda, ]\[options] ) Returns a pseudorandom number generator (PRNG) for generating pseudorandom numbers drawn from a [Poisson][poisson] distribution. ```javascript var rand = poisson.factory(); var r = rand( 15.0 ); // returns ``` If provided `lambda`, the returned generator returns random variates from the specified distribution. ```javascript var rand = poisson.factory( 10.0 ); var r = rand(); // returns r = rand(); // returns ``` If not provided `lambda`, the returned generator requires that `lambda` be provided at each invocation. ```javascript var rand = poisson.factory(); var r = rand( 4.0 ); // returns r = rand( 3.14 ); // returns ``` The function accepts the following `options`: - **prng**: pseudorandom number generator for generating uniformly distributed pseudorandom numbers on the interval `[0,1)`. If provided, the function **ignores** both the `state` and `seed` options. In order to seed the returned pseudorandom number generator, one must seed the provided `prng` (assuming the provided `prng` is seedable). - **seed**: pseudorandom number generator seed. - **state**: a [`Uint32Array`][@stdlib/array/uint32] containing pseudorandom number generator state. If provided, the function ignores the `seed` option. - **copy**: `boolean` indicating whether to copy a provided pseudorandom number generator state. Setting this option to `false` allows sharing state between two or more pseudorandom number generators. Setting this option to `true` ensures that a returned generator has exclusive control over its internal state. Default: `true`. To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the `prng` option. ```javascript var minstd = require( '@stdlib/random-base-minstd' ); var rand = poisson.factory({ 'prng': minstd.normalized }); var r = rand( 3.0 ); // returns ``` To seed a pseudorandom number generator, set the `seed` option. ```javascript var rand1 = poisson.factory({ 'seed': 12345 }); var r1 = rand1( 3.0 ); // returns var rand2 = poisson.factory( 3.0, { 'seed': 12345 }); var r2 = rand2(); // returns var bool = ( r1 === r2 ); // returns true ``` To return a generator having a specific initial state, set the generator `state` option. ```javascript var rand; var bool; var r; var i; // Generate pseudorandom numbers, thus progressing the generator state: for ( i = 0; i < 1000; i++ ) { r = poisson( 10.0 ); } // Create a new PRNG initialized to the current state of `poisson`: rand = poisson.factory({ 'state': poisson.state }); // Test that the generated pseudorandom numbers are the same: bool = ( rand( 10.0 ) === poisson( 10.0 ) ); // returns true ``` #### poisson.NAME The generator name. ```javascript var str = poisson.NAME; // returns 'poisson' ``` #### poisson.PRNG The underlying pseudorandom number generator. ```javascript var prng = poisson.PRNG; // returns ``` #### poisson.seed The value used to seed `poisson()`. ```javascript var rand; var r; var i; // Generate pseudorandom values... for ( i = 0; i < 100; i++ ) { r = poisson( 2.0 ); } // Generate the same pseudorandom values... rand = poisson.factory( 2.0, { 'seed': poisson.seed }); for ( i = 0; i < 100; i++ ) { r = rand(); } ``` If provided a PRNG for uniformly distributed numbers, this value is `null`. ```javascript var rand = poisson.factory({ 'prng': Math.random }); var seed = rand.seed; // returns null ``` #### poisson.seedLength Length of generator seed. ```javascript var len = poisson.seedLength; // returns ``` If provided a PRNG for uniformly distributed numbers, this value is `null`. ```javascript var rand = poisson.factory({ 'prng': Math.random }); var len = rand.seedLength; // returns null ``` #### poisson.state Writable property for getting and setting the generator state. ```javascript var r = poisson( 10.0 ); // returns r = poisson( 10.0 ); // returns // ... // Get a copy of the current state: var state = poisson.state; // returns r = poisson( 10.0 ); // returns r = poisson( 10.0 ); // returns // Reset the state: poisson.state = state; // Replay the last two pseudorandom numbers: r = poisson( 10.0 ); // returns r = poisson( 10.0 ); // returns // ... ``` If provided a PRNG for uniformly distributed numbers, this value is `null`. ```javascript var rand = poisson.factory({ 'prng': Math.random }); var state = rand.state; // returns null ``` #### poisson.stateLength Length of generator state. ```javascript var len = poisson.stateLength; // returns ``` If provided a PRNG for uniformly distributed numbers, this value is `null`. ```javascript var rand = poisson.factory({ 'prng': Math.random }); var len = rand.stateLength; // returns null ``` #### poisson.byteLength Size (in bytes) of generator state. ```javascript var sz = poisson.byteLength; // returns ``` If provided a PRNG for uniformly distributed numbers, this value is `null`. ```javascript var rand = poisson.factory({ 'prng': Math.random }); var sz = rand.byteLength; // returns null ``` #### poisson.toJSON() Serializes the pseudorandom number generator as a JSON object. ```javascript var o = poisson.toJSON(); // returns { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] } ``` If provided a PRNG for uniformly distributed numbers, this method returns `null`. ```javascript var rand = poisson.factory({ 'prng': Math.random }); var o = rand.toJSON(); // returns null ```

## Notes - If PRNG state is "shared" (meaning a state array was provided during PRNG creation and **not** copied) and one sets the generator state to a state array having a different length, the PRNG does **not** update the existing shared state and, instead, points to the newly provided state array. In order to synchronize PRNG output according to the new shared state array, the state array for **each** relevant PRNG must be **explicitly** set. - If PRNG state is "shared" and one sets the generator state to a state array of the same length, the PRNG state is updated (along with the state of all other PRNGs sharing the PRNG's state array).

## Examples ```javascript var poisson = require( '@stdlib/random-base-poisson' ); var seed; var rand; var i; // Generate pseudorandom numbers... for ( i = 0; i < 100; i++ ) { console.log( poisson( 8.0 ) ); } // Create a new pseudorandom number generator... seed = 1234; rand = poisson.factory( 0.8, { 'seed': seed }); for ( i = 0; i < 100; i++ ) { console.log( rand() ); } // Create another pseudorandom number generator using a previous seed... rand = poisson.factory( 8.0, { 'seed': poisson.seed }); for ( i = 0; i < 100; i++ ) { console.log( rand() ); } ```

## References - Knuth, Donald E. 1997. _The Art of Computer Programming, Volume 2 (3rd Ed.): Seminumerical Algorithms_. Boston, MA, USA: Addison-Wesley Longman Publishing Co., Inc. - Hörmann, W. 1993. "The transformed rejection method for generating Poisson random variables." _Insurance: Mathematics and Economics_ 12 (1): 39–45. doi:[10.1016/0167-6687(93)90997-4][@hormann:1993b].

* * * ## Notice This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib]. #### Community [![Chat][chat-image]][chat-url] --- ## License See [LICENSE][stdlib-license]. ## Copyright Copyright © 2016-2025. The Stdlib [Authors][stdlib-authors].

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Website: https://stdlib.io
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Standard library for JavaScript.

Citation (CITATION.cff)

cff-version: 1.2.0
title: stdlib
message: >-
  If you use this software, please cite it using the
  metadata from this file.

type: software

authors:
  - name: The Stdlib Authors
    url: https://github.com/stdlib-js/stdlib/graphs/contributors

repository-code: https://github.com/stdlib-js/stdlib
url: https://stdlib.io

abstract: |
  Standard library for JavaScript and Node.js.

keywords:
  - JavaScript
  - Node.js
  - TypeScript
  - standard library
  - scientific computing
  - numerical computing
  - statistical computing

license: Apache-2.0 AND BSL-1.0

date-released: 2016

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npmjs.org: @stdlib/random-base-poisson

Poisson distributed random numbers.

Homepage: https://stdlib.io
License: Apache-2.0
Latest release: 0.2.1
published almost 2 years ago

Versions: 9
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Dependent Repositories: 17
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@stdlib/random-base-poisson

Science Score: 57.0%

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Poisson Random Numbers

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