npm package: @stdlib/stats-base-dists-f-quantile
Description: F distribution quantile function.
Author: The Stdlib Authors
Latest version: 0.2.3

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# Quantile Function

[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url] <!-- [![dependencies][dependencies-image]][dependencies-url] -->

> [F][f-distribution] distribution [quantile function][quantile-function].

<section class="intro">

The [quantile function][quantile-function] for a [F][f-distribution] random variable is

<!-- <equation class="equation" label="eq:f_quantile_function" align="center" raw="Q(p;d_1,d_2) = \,\inf\left\{ x\in [0,+\infty) : p \le F(x;d_1,d_2) \right\}" alt="Quantile function for an F distribution."> -->

<div class="equation" align="center" data-raw-text="Q(p;d_1,d_2) = \,\inf\left\{ x\in [0,+\infty) : p \le F(x;d_1,d_2) \right\}" data-equation="eq:f_quantile_function">
    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@591cf9d5c3a0cd3c1ceec961e5c49d73a68374cb/lib/node_modules/@stdlib/stats/base/dists/f/quantile/docs/img/equation_f_quantile_function.svg" alt="Quantile function for an F distribution.">
    <br>
</div>

<!-- </equation> -->

for `0 <= p < 1`, where `d1` is the numerator degrees of freedom, `d2` is the denominator degrees of freedom and `F` the cumulative distribution function (CDF) of the F distribution.

</section>

<!-- /.intro -->

<section class="installation">

## Installation

```bash
npm install @stdlib/stats-base-dists-f-quantile
```

</section>

<section class="usage">

## Usage

```javascript
var quantile = require( '@stdlib/stats-base-dists-f-quantile' );
```

#### quantile( p, d1, d2 )

Evaluates the [quantile function][quantile-function] for a [F][f-distribution] distribution with parameters `d1` (numerator degrees of freedom) and `d2` (denominator degrees of freedom).

```javascript
var y = quantile( 0.5, 1.0, 1.0 );
// returns 1.0

y = quantile( 0.2, 4.0, 2.0 );
// returns ~0.405

y = quantile( 0.8, 4.0, 2.0 );
// returns ~4.236
```

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( 0.0, NaN, 1.0 );
// returns NaN

y = quantile( 0.0, 1.0, NaN );
// returns NaN
```

If provided `d1 <= 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 `d2 <= 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( d1, d2 )

Returns a function for evaluating the quantile function of an [F][f-distribution] distribution with parameters `d1` (numerator degrees of freedom) and `d2` (denominator degrees of freedom).

```javascript
var myquantile = quantile.factory( 10.0, 2.0 );

var y = myquantile( 0.2 );
// returns ~0.527

y = myquantile( 0.8 );
// returns ~4.382
```

</section>

<!-- /.usage -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
var uniform = require( '@stdlib/random-array-uniform' );
var logEachMap = require( '@stdlib/console-log-each-map' );
var quantile = require( '@stdlib/stats-base-dists-f-quantile' );

var opts = {
    'dtype': 'float64'
};
var p = uniform( 10, 0.0, 1.0, opts );
var d1 = uniform( 10, 0.0, 10.0, opts );
var d2 = uniform( 10, 0.0, 10.0, opts );

logEachMap( 'p: %0.4f, d1: %0.4f, d2: %0.4f, Q(p;d1,d2): %0.4f', p, d1, d2, quantile );
```

</section>

<!-- /.examples -->

<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->

<section class="related">

</section>

<!-- /.related -->

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<section class="main-repo" >

* * *

## Notice

This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib].

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---

## License

See [LICENSE][stdlib-license].


## Copyright

Copyright &copy; 2016-2026. The Stdlib [Authors][stdlib-authors].

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[f-distribution]: https://en.wikipedia.org/wiki/F_distribution

[quantile-function]: https://en.wikipedia.org/wiki/Quantile_function

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