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@stdlib/stats-base-dists-rayleigh-quantile

v0.2.2

Published

Rayleigh distribution quantile function.

Downloads

381

Readme

Quantile Function

NPM version Build Status Coverage Status

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

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License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.