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Erlang distribution.
import erlang from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-erlang@deno/mod.js';You can also import the following named exports from the package:
import { Erlang, cdf, entropy, kurtosis, logpdf, mean, mgf, mode, pdf, quantile, skewness, stdev, variance } from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-erlang@deno/mod.js';Erlang distribution.
var dist = erlang;
// returns {...}The namespace contains the following distribution functions:
cdf( x, k, lambda ): Erlang distribution cumulative distribution function.logpdf( x, k, lambda ): evaluate the natural logarithm of the probability density function (PDF) for an Erlang distribution.mgf( t, k, lambda ): Erlang distribution moment-generating function (MGF).pdf( x, k, lambda ): Erlang distribution probability density function (PDF).quantile( p, k, lambda ): Erlang distribution quantile function.
The namespace contains the following functions for calculating distribution properties:
entropy( k, lambda ): Erlang distribution differential entropy.kurtosis( k, lambda ): Erlang distribution excess kurtosis.mean( k, lambda ): Erlang distribution expected value.mode( k, lambda ): Erlang distribution mode.skewness( k, lambda ): Erlang distribution skewness.stdev( k, lambda ): Erlang distribution standard deviation.variance( k, lambda ): Erlang distribution variance.
The namespace contains a constructor function for creating an Erlang distribution object.
Erlang( [k, lambda] ): Erlang distribution constructor.
var Erlang = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-erlang' ).Erlang;
var dist = new Erlang( 2, 4.0 );
var y = dist.logpdf( 0.8 );
// returns ~-0.65import objectKeys from 'https://cdn.jsdelivr.net/gh/stdlib-js/utils-keys@deno/mod.js';
import erlang from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-erlang@deno/mod.js';
console.log( objectKeys( erlang ) );This package is part of stdlib, a standard library 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.
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