stdlib-js
<summary>
About stdlib...
</summary>
We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
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Quantile Function
[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url]
[Beta][beta-distribution] distribution [quantile function][quantile-function].
0 <= p <= 1, where alpha > 0 is the first shape parameter and beta > 0 is the second shape parameter and F(x;alpha,beta) denotes the cumulative distribution function of a [beta][beta-distribution] random variable with parameters alpha and beta.
bash
npm install @stdlib/stats-base-dists-beta-quantile
javascript
var quantile = require( '@stdlib/stats-base-dists-beta-quantile' );
#### quantile( p, alpha, beta )
Evaluates the [quantile function][quantile-function] for a [beta][beta-distribution] distribution with parameters alpha (first shape parameter) and beta (second shape parameter).
javascript
var y = quantile( 0.8, 2.0, 1.0 );
// returns ~0.894
y = quantile( 0.5, 4.0, 2.0 );
// returns ~0.686
If provided a probability p outside the interval [0,1], the function returns NaN.
javascript
var y = quantile( 1.9, 1.0, 1.0 );
// returns NaN
y = quantile( -0.1, 1.0, 1.0 );
// returns NaN
If provided NaN as any argument, the function returns NaN.
javascript
var y = quantile( NaN, 1.0, 1.0 );
// returns NaN
y = quantile( 0.5, NaN, 1.0 );
// returns NaN
y = quantile( 0.5, 1.0, NaN );
// returns NaN
If provided alpha <= 0, the function returns NaN.
javascript
var y = quantile( 0.4, -1.0, 1.0 );
// returns NaN
y = quantile( 0.4, 0.0, 1.0 );
// returns NaN
If provided beta <= 0, the function returns NaN.
javascript
var y = quantile( 0.4, 1.0, -1.0 );
// returns NaN
y = quantile( 0.4, 1.0, 0.0 );
// returns NaN
#### quantile.factory( alpha, beta )
Returns a function for evaluating the [quantile function][quantile-function] of a [beta][beta-distribution] distribution with parameters alpha (first shape parameter) and beta (second shape parameter).
javascript
var myquantile = quantile.factory( 2.0, 2.0 );
var y = myquantile( 0.8 );
// returns ~0.713
y = myquantile( 0.4 );
// returns ~0.433
javascript
var randu = require( '@stdlib/random-base-randu' );
var EPS = require( '@stdlib/constants-float64-eps' );
var quantile = require( '@stdlib/stats-base-dists-beta-quantile' );
var alpha;
var beta;
var p;
var y;
var i;
for ( i = 0; i < 10; i++ ) {
p = randu();
alpha = ( randu()*5.0 ) + EPS;
beta = ( randu()*5.0 ) + EPS;
y = quantile( p, alpha, beta );
console.log( 'p: %d, α: %d, β: %d, Q(p;α,β): %d', p.toFixed( 4 ), alpha.toFixed( 4 ), beta.toFixed( 4 ), y.toFixed( 4 ) );
}
