@stdlib/stats-base-dists-laplace-quantile
v0.2.2
Published
Laplace distribution quantile function.
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Quantile Function
Laplace distribution quantile function.
The quantile function for a Laplace random variable is
for 0 <= p < 1
, where mu
is the location parameter and b > 0
is the scale parameter.
Installation
npm install @stdlib/stats-base-dists-laplace-quantile
Usage
var quantile = require( '@stdlib/stats-base-dists-laplace-quantile' );
quantile( p, mu, b )
Evaluates the quantile function for a Laplace distribution with parameters mu
(location parameter) and b > 0
(scale parameter).
var y = quantile( 0.8, 0.0, 1.0 );
// returns ~0.916
y = quantile( 0.5, 4.0, 2.0 );
// returns 4
If provided a probability p
outside the interval [0,1]
, the function returns NaN
.
var y = quantile( 1.9, 0.0, 1.0 );
// returns NaN
y = quantile( -0.1, 0.0, 1.0 );
// returns NaN
If provided NaN
as any argument, the function returns NaN
.
var y = quantile( NaN, 0.0, 1.0 );
// returns NaN
y = quantile( 0.0, NaN, 1.0 );
// returns NaN
y = quantile( 0.0, 0.0, NaN );
// returns NaN
If provided b <= 0
, the function returns NaN
.
var y = quantile( 0.4, 0.0, -1.0 );
// returns NaN
y = quantile( 0.4, 0.0, 0.0 );
// returns NaN
quantile.factory( mu, b )
Returns a function for evaluating the quantile function of a Laplace distribution with parameters mu
and b > 0
.
var myquantile = quantile.factory( 10.0, 2.0 );
var y = myquantile( 0.5 );
// returns 10.0
y = myquantile( 0.8 );
// returns ~11.833
Examples
var randu = require( '@stdlib/random-base-randu' );
var quantile = require( '@stdlib/stats-base-dists-laplace-quantile' );
var mu;
var b;
var p;
var y;
var i;
for ( i = 0; i < 100; i++ ) {
p = randu();
mu = randu() * 10.0;
b = randu() * 10.0;
y = quantile( p, mu, b );
console.log( 'p: %d, µ: %d, b: %d, Q(p;µ,b): %d', p.toFixed( 4 ), mu.toFixed( 4 ), b.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.