Huge News!Announcing our $40M Series B led by Abstract Ventures.Learn More
Socket
Sign inDemoInstall
Socket

@stdlib/stats-base-dists-poisson-logpmf

Package Overview
Dependencies
Maintainers
4
Versions
11
Alerts
File Explorer

Advanced tools

Socket logo

Install Socket

Detect and block malicious and high-risk dependencies

Install

@stdlib/stats-base-dists-poisson-logpmf

Natural logarithm of the probability mass function (PMF) for a Poisson distribution.

  • 0.0.3
  • Source
  • npm
  • Socket score

Version published
Weekly downloads
1K
increased by3.95%
Maintainers
4
Weekly downloads
 
Created
Source

Logarithm of Probability Mass Function

NPM version Build Status Coverage Status dependencies

Evaluate the natural logarithm of the probability mass function (PMF) for a Poisson distribution.

The probability mass function (PMF) for a Poisson random variable is

Probability mass function (PMF) for a Poisson distribution.

where lambda > 0 is the mean parameter.

Installation

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

Usage

var logpmf = require( '@stdlib/stats-base-dists-poisson-logpmf' );
logpmf( x, lambda )

Evaluates the natural logarithm of the probability mass function (PMF) for a Poisson distribution with mean parameter lambda.

var y = logpmf( 4.0, 3.0 );
// returns ~-1.784

y = logpmf( 1.0, 3.0 );
// returns ~-1.901

y = logpmf( -1.0, 2.0 );
// returns -Infinity

If provided NaN as any argument, the function returns NaN.

var y = logpmf( NaN, 2.0 );
// returns NaN

y = logpmf( 0.0, NaN );
// returns NaN

If provided a negative mean parameter lambda, the function returns NaN.

var y = logpmf( 2.0, -1.0 );
// returns NaN

y = logpmf( 4.0, -2.0 );
// returns NaN

If provided lambda = 0, the function evaluates the natural logarithm of the PMF of a degenerate distribution centered at 0.0.

var y = logpmf( 2.0, 0.0 );
// returns -Infinity

y = logpmf( 0.0, 0.0 );
// returns 0.0
logpmf.factory( lambda )

Returns a function for evaluating the natural logarithm of the probability mass function (PMF) for a Poisson distribution with mean parameter lambda.

var mylogpmf = logpmf.factory( 1.0 );
var y = mylogpmf( 3.0 );
// returns ~-2.792

y = mylogpmf( 1.0 );
// returns ~-1.0

Examples

var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var logpmf = require( '@stdlib/stats-base-dists-poisson-logpmf' );

var lambda;
var x;
var y;
var i;

for ( i = 0; i < 10; i++ ) {
    x = round( randu() * 10.0 );
    lambda = randu() * 10.0;
    y = logpmf( x, lambda );
    console.log( 'x: %d, λ: %d, ln(P(X=x;λ)): %d', x, lambda.toFixed( 4 ), y.toFixed( 4 ) );
}

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

Chat


License

See LICENSE.

Copyright © 2016-2021. The Stdlib Authors.

Keywords

FAQs

Package last updated on 27 Jun 2021

Did you know?

Socket

Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.

Install

Related posts

SocketSocket SOC 2 Logo

Product

  • Package Alerts
  • Integrations
  • Docs
  • Pricing
  • FAQ
  • Roadmap
  • Changelog

Packages

npm

Stay in touch

Get open source security insights delivered straight into your inbox.


  • Terms
  • Privacy
  • Security

Made with ⚡️ by Socket Inc