@stdlib/stats-base-dists-chisquare-quantile
v0.2.2
Published
Chi-squared distribution quantile function.
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Quantile Function
Chi-squared distribution quantile function.
The quantile function for a chi-squared random variable is
for 0 <= p < 1
, where k
is the degrees of freedom and P^{-1}
is the inverse of the lower, regularized incomplete gamma function.
Installation
npm install @stdlib/stats-base-dists-chisquare-quantile
Usage
var quantile = require( '@stdlib/stats-base-dists-chisquare-quantile' );
quantile( p, k )
Evaluates the quantile function for a chi-squared distribution with degrees of freedom k
.
var y = quantile( 0.8, 1.0 );
// returns ~1.642
y = quantile( 0.5, 4.0 );
// returns ~3.357
y = quantile( 0.8, 0.1 );
// returns ~0.014
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( 0.2, NaN );
// returns NaN
If provided k < 0
, the function returns NaN
.
var y = quantile( 0.4, -1.0 );
// returns NaN
If provided k = 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( k )
Returns a function for evaluating the quantile function of a chi-squared distribution with degrees of freedom k
.
var myquantile = quantile.factory( 0.4 );
var y = myquantile( 0.9 );
// returns ~1.21
y = myquantile( 1.0 );
// returns Infinity
Examples
var randu = require( '@stdlib/random-base-randu' );
var quantile = require( '@stdlib/stats-base-dists-chisquare-quantile' );
var k;
var p;
var y;
var i;
for ( i = 0; i < 20; i++ ) {
p = randu();
k = randu() * 10.0;
y = quantile( p, k );
console.log( 'p: %d, k: %d, Q(p;k): %d', p.toFixed( 4 ), k.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.