@stdlib/stats-base-dists-rayleigh-quantile
v0.2.2
Published
Rayleigh distribution quantile function.
Downloads
327
Readme
Quantile Function
Rayleigh distribution quantile function.
The quantile function for a Rayleigh random variable is
for 0 <= p < 1
, where sigma > 0
is the scale parameter.
Installation
npm install @stdlib/stats-base-dists-rayleigh-quantile
Usage
var quantile = require( '@stdlib/stats-base-dists-rayleigh-quantile' );
quantile( p, sigma )
Evaluates the quantile function for a Rayleigh distribution with parameter sigma
(scale parameter).
var y = quantile( 0.8, 1.0 );
// returns ~1.794
y = quantile( 0.5, 4.0 );
// returns ~4.71
If provided a probability p
outside the interval [0,1]
, the function returns NaN
.
var y = quantile( 1.9, 1.0 );
// returns NaN
y = quantile( -0.1, 1.0 );
// returns NaN
If provided NaN
as any argument, the function returns NaN
.
var y = quantile( NaN, 1.0 );
// returns NaN
y = quantile( 0.0, NaN);
// returns NaN
If provided sigma < 0
, the function returns NaN
.
var y = quantile( 0.4, -1.0 );
// returns NaN
If provided sigma = 0
, the function evaluates the quantile function of a degenerate distribution centered at 0
.
var y = quantile( 0.3, 0.0 );
// returns 0.0
y = quantile( 0.9, 0.0 );
// returns 0.0
quantile.factory( sigma )
Returns a function for evaluating the quantile function of a Rayleigh distribution with scale parameter sigma
.
var myQuantile = quantile.factory( 0.4 );
y = myQuantile( 0.4 );
// returns ~0.404
y = myQuantile( 1.0 );
// returns Infinity
Examples
var randu = require( '@stdlib/random-base-randu' );
var quantile = require( '@stdlib/stats-base-dists-rayleigh-quantile' );
var sigma;
var p;
var y;
var i;
for ( i = 0; i < 10; i++ ) {
p = randu();
sigma = randu() * 10.0;
y = quantile( p, sigma );
console.log( 'p: %d, σ: %d, Q(p;σ): %d', p.toFixed( 4 ), sigma.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
License
See LICENSE.
Copyright
Copyright © 2016-2024. The Stdlib Authors.