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Rayleigh distribution.
import rayleigh from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-rayleigh@deno/mod.js';You can also import the following named exports from the package:
import { Rayleigh, cdf, entropy, kurtosis, logcdf, logpdf, mean, median, mgf, mode, pdf, quantile, skewness, stdev, variance } from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-rayleigh@deno/mod.js';Rayleigh distribution.
var dist = rayleigh;
// returns {...}The namespace contains the following distribution functions:
cdf( x, sigma ): Rayleigh distribution cumulative distribution function.logcdf( x, sigma ): Rayleigh distribution logarithm of cumulative distribution function.logpdf( x, sigma ): Rayleigh distribution logarithm of probability density function (PDF).mgf( t, sigma ): Rayleigh distribution moment-generating function (MGF).pdf( x, sigma ): Rayleigh distribution probability density function (PDF).quantile( p, sigma ): Rayleigh distribution quantile function.
The namespace contains the following functions for calculating distribution properties:
entropy( sigma ): Rayleigh distribution differential entropy.kurtosis( sigma ): Rayleigh distribution excess kurtosis.mean( sigma ): Rayleigh distribution expected value.median( sigma ): Rayleigh distribution median.mode( sigma ): Rayleigh distribution mode.skewness( sigma ): Rayleigh distribution skewness.stdev( sigma ): Rayleigh distribution standard deviation.variance( sigma ): Rayleigh distribution variance.
The namespace contains a constructor function for creating a Rayleigh distribution object.
Rayleigh( [sigma] ): Rayleigh distribution constructor.
var Rayleigh = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-rayleigh' ).Rayleigh;
var dist = new Rayleigh( 2.0 );
var y = dist.pdf( 0.8 );
// returns ~0.185import rayleigh from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-rayleigh@deno/mod.js';
/*
* The Rayleigh distribution can be used to model wind speeds.
* Let's consider a scenario where we want to estimate various properties related to wind speeds.
*/
// Set the Rayleigh distribution parameter (scale parameter):
var s = 10.0;
// Calculate mean, variance, and standard deviation of the Rayleigh distribution:
console.log( rayleigh.mean( s ) );
// => ~12.533
console.log( rayleigh.variance( s ) );
// => ~42.920
console.log( rayleigh.stdev( s ) );
// => ~6.551
// Evaluate the Probability Density Function (PDF) for a specific wind speed:
var w = 15.0;
console.log( rayleigh.pdf( w, s ) );
// => ~0.049
// Determine Cumulative Distribution Function (CDF) for wind speeds up to a certain value:
var t = 15.0;
console.log( rayleigh.cdf( t, s ) );
// => ~0.675
// Calculate the probability of wind speeds exceeding the threshold:
var p = 1.0 - rayleigh.cdf( t, s );
console.log( 'Probability of wind speeds exceeding ' + t + ' m/s:', p );
// Find the wind speed at which there's a 70% chance it won't exceed using the Quantile function:
var c = 0.7;
console.log( rayleigh.quantile( c, s ) );
// => ~15.518This 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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