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@stdlib/stats-base-dists-poisson

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@stdlib/stats-base-dists-poisson

Poisson distribution.

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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

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Poisson distribution.

Installation

npm install @stdlib/stats-base-dists-poisson

Usage

var poisson = require( '@stdlib/stats-base-dists-poisson' );
poisson

Poisson distribution.

var dist = poisson;
// returns {...}

The namespace contains the following distribution functions:

The namespace contains the following functions for calculating distribution properties:

The namespace contains a constructor function for creating a Poisson distribution object.

var Poisson = require( '@stdlib/stats-base-dists-poisson' ).Poisson;

var dist = new Poisson( 2.0 );

var y = dist.pmf( 3.0 );
// returns ~0.18

y = dist.pmf( 2.3 );
// returns 0.0

Examples

var poisson = require( '@stdlib/stats-base-dists-poisson' );

/*
* Let's take a customer service center example: average rate of customer inquiries is 3 per hour.
* This situation can be modeled using a Poisson distribution with λ = 3
*/

var lambda = 3;

// Mean can be used to calculate the average number of inquiries per hour:
console.log( poisson.mean( lambda ) );
// => 3

// Standard deviation can be used to calculate the measure of the spread of inquiries around the mean:
console.log( poisson.stdev( lambda ) );
// => ~1.7321

// Variance can be used to calculate the variability of the number of inquiries:
console.log( poisson.variance( lambda ) );
// => 3

// PMF can be used to calculate specific number of inquiries in an hour:
console.log( poisson.pmf( 4, lambda ) );
// => ~0.1680

// CDF can be used to calculate probability up to certain number of inquiries in an hour:
console.log( poisson.cdf( 2, lambda ) );
// => ~0.4232

// Quantile can be used to calculate the number of inquiries at which you can be 80% confident that the actual number will not exceed.
console.log( poisson.quantile( 0.8, lambda ) );
// => 4

// MGF can be used for more advanced statistical analyses and generating moments of the distribution.
console.log( poisson.mgf( 1.0, lambda ) );
// => ~173.2690

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.

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License

See LICENSE.

Copyright © 2016-2024. The Stdlib Authors.

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Package last updated on 28 Jul 2024

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