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Merge branch 'develop' of https://github.com/stdlib-js/stdlib into develop
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‎docs/migration-guides/simple-statistics/data/simple_statistics_3_0_0.csv‎

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@@ -53,7 +53,7 @@ ckmeans,(planned)
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equalIntervalBreaks,N/A
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chunk,(planned)
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mixin,(planned)
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chiSquaredGoodnessOfFit,math/statistics/chigof
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chiSquaredGoodnessOfFit,math/statistics/chi2gof
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epsilon,math/constants/float64-epsilon
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factorial,math/base/special/factorial
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uniqueCountSorted,N/A

‎lib/node_modules/@stdlib/math/base/dist/betaprime/lib/index.js‎

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@@ -54,6 +54,15 @@ setReadOnly( betaprime, 'mean', require( '@stdlib/math/base/dist/betaprime/mean'
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*/
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setReadOnly( betaprime, 'pdf', require( '@stdlib/math/base/dist/betaprime/pdf' ) );
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/**
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* @name quantile
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* @memberof betaprime
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* @readonly
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* @type {Function}
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* @see {@link module:@stdlib/math/base/dist/betaprime/quantile}
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*/
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setReadOnly( betaprime, 'quantile', require( '@stdlib/math/base/dist/betaprime/quantile' ) );
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/**
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* @name skewness
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* @memberof betaprime

‎lib/node_modules/@stdlib/math/base/dist/betaprime/quantile/README.md‎

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# Quantile Function
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> [Beta prime][betaprime] distribution [quantile function][quantile-function].
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<section class="intro">
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The [quantile function][quantile-function] for a [beta prime][betaprime] random variable with first shape parameter `α > 0` and second shape parameter `β > 0` is
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<!-- <equation class="equation" label="eq:betaprime_quantile_function" align="center" raw="Q(p;\alpha,\beta)\,= \frac{G^{-1}(p)}{1-G^{-1}(p)}" alt="Quantile function for a beta prime distribution."> -->
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<div class="equation" align="center" data-raw-text="Q(p;\alpha,\beta)\,= \frac{G^{-1}(p)}{1-G^{-1}(p)}" data-equation="eq:betaprime_quantile_function">
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<img src="" alt="Quantile function for a beta prime distribution.">
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<br>
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</div>
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<!-- </equation> -->
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for `0 <= p <= 1`, where `G^-1` denotes the quantile function of a [beta][beta] random variable with parameters `α` and `β`.
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</section>
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<!-- /.intro -->
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<section class="usage">
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## Usage
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``` javascript
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var quantile = require( '@stdlib/math/base/dist/betaprime/quantile' );
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```
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#### quantile( p, alpha, beta )
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Evaluates the [quantile function][quantile-function] for a [beta prime][betaprime] distribution with parameters `alpha` (first shape parameter) and `beta` (second shape parameter).
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``` javascript
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var y = quantile( 0.8, 2.0, 1.0 );
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// returns ~2.994
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y = quantile( 0.5, 4.0, 2.0 );
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// returns ~1.836
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```
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If provided a probability `p` outside the interval `[0,1]`, the function returns `NaN`.
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``` javascript
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var y = quantile( 1.9, 1.0, 1.0 );
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// returns NaN
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y = quantile( -0.1, 1.0, 1.0 );
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// returns NaN
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```
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If provided `NaN` as any argument, the function returns `NaN`.
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``` javascript
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var y = quantile( NaN, 1.0, 1.0 );
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// returns NaN
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y = quantile( 0.5, NaN, 1.0 );
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// returns NaN
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y = quantile( 0.5, 1.0, NaN );
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// returns NaN
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```
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If provided `alpha <= 0`, the function returns `NaN`.
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``` javascript
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var y = quantile( 0.4, -1.0, 1.0 );
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// returns NaN
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y = quantile( 0.4, 0.0, 1.0 );
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// returns NaN
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```
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If provided `beta <= 0`, the function returns `NaN`.
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``` javascript
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var y = quantile( 0.4, 1.0, -1.0 );
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// returns NaN
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y = quantile( 0.4, 1.0, 0.0 );
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// returns NaN
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```
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#### quantile.factory( alpha, beta )
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Returns a function for evaluating the [quantile function][quantile-function] of a [beta prime][betaprime] distribution with parameters `alpha` (first shape parameter) and `beta` (second shape parameter).
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``` javascript
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var myQuantile = quantile.factory( 2.0, 2.0 );
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var y = myQuantile( 0.8 );
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// returns ~2.483
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y = myQuantile( 0.4 );
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// returns ~0.763
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```
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</section>
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<!-- /.usage -->
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<section class="examples">
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## Examples
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``` javascript
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var randu = require( '@stdlib/math/base/random/randu' );
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var EPS = require( '@stdlib/math/constants/float64-eps' );
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var quantile = require( '@stdlib/math/base/dist/betaprime/quantile' );
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var alpha;
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var beta;
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var p;
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var y;
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var i;
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for ( i = 0; i < 10; i++ ) {
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p = randu();
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alpha = ( randu()*5.0 ) + EPS;
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beta = ( randu()*5.0 ) + EPS;
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y = quantile( p, alpha, beta );
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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 ) );
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}
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```
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</section>
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<!-- /.examples -->
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<section class="links">
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[beta]: https://en.wikipedia.org/wiki/Beta_distribution
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[betaprime]: https://en.wikipedia.org/wiki/Beta_prime_distribution
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[quantile-function]: https://en.wikipedia.org/wiki/Quantile_function
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</section>
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<!-- /.links -->

‎lib/node_modules/@stdlib/math/base/dist/betaprime/quantile/benchmark/benchmark.js‎

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'use strict';
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// MODULES //
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var bench = require( '@stdlib/bench' );
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var randu = require( '@stdlib/math/base/random/randu' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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var EPS = require( '@stdlib/math/constants/float64-eps' );
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var pkg = require( './../package.json' ).name;
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var quantile = require( './../lib' );
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// MAIN //
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bench( pkg, function benchmark( b ) {
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var alpha;
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var beta;
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var p;
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var y;
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var i;
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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p = randu();
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alpha = ( randu()*100.0 ) + EPS;
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beta = ( randu()*100.0 ) + EPS;
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y = quantile( p, alpha, beta );
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if ( isnan( y ) ) {
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b.fail( 'should not return NaN' );
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}
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}
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b.toc();
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if ( isnan( y ) ) {
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b.fail( 'should not return NaN' );
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}
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b.pass( 'benchmark finished' );
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b.end();
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});
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bench( pkg+':factory', function benchmark( b ) {
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var myQuantile;
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var alpha;
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var beta;
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var p;
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var y;
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var i;
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alpha = 100.56789;
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beta = 55.54321;
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myQuantile = quantile.factory( alpha, beta );
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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p = randu();
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y = myQuantile( p );
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if ( isnan( y ) ) {
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b.fail( 'should not return NaN' );
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}
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}
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b.toc();
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if ( isnan( y ) ) {
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b.fail( 'should not return NaN' );
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}
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b.pass( 'benchmark finished' );
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b.end();
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});

‎lib/node_modules/@stdlib/math/base/dist/betaprime/quantile/docs/repl.txt‎

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{{alias}}( p, α, β )
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Evaluates the quantile function for a beta prime distribution with first
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shape parameter `α` and second shape parameter `β` at a probability `p`.
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If `p < 0` or `p > 1`, the function returns `NaN`.
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If provided `NaN` as any argument, the function returns `NaN`.
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If `α <= 0` or `β <= 0`, the function returns `NaN`.
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Parameters
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----------
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p: number
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Input value (probability).
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α: number
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First shape parameter.
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β: number
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Second shape parameter.
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Returns
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-------
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out: number
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Evaluated quantile function.
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Examples
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--------
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> var y = {{alias}}( 0.8, 2.0, 1.0 )
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~8.472
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> y = {{alias}}( 0.5, 4.0, 2.0 )
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~2.187
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> y = {{alias}}( 1.1, 1.0, 1.0 )
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NaN
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> y = {{alias}}( -0.2, 1.0, 1.0 )
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NaN
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> y = {{alias}}( NaN, 1.0, 1.0 )
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NaN
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> y = {{alias}}( 0.5, NaN, 1.0 )
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NaN
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> y = {{alias}}( 0.5, 1.0, NaN )
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NaN
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> y = {{alias}}( 0.5, -1.0, 1.0 )
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NaN
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> y = {{alias}}( 0.5, 1.0, -1.0 )
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NaN
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{{alias}}.factory( α, β )
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Returns a function for evaluating the quantile function of a beta prime
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distribution with first shape parameter `α` and second shape parameter `β`.
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Parameters
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----------
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α: number
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First shape parameter.
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β: number
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Second shape parameter.
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Returns
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-------
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quantile: Function
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Quantile function.
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Examples
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--------
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> var myQuantile = {{alias}}.factory( 2.0, 2.0 );
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> y = myQuantile( 0.8 )
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~2.483
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> y = myQuantile( 0.4 )
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~0.763
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See Also
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--------
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‎lib/node_modules/@stdlib/math/base/dist/betaprime/quantile/examples/index.js‎

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'use strict';
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var randu = require( '@stdlib/math/base/random/randu' );
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var EPS = require( '@stdlib/math/constants/float64-eps' );
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var quantile = require( './../lib' );
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var alpha;
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var beta;
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var p;
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var y;
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var i;
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for ( i = 0; i < 10; i++ ) {
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p = randu();
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alpha = ( randu()*5.0 ) + EPS;
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beta = ( randu()*5.0 ) + EPS;
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y = quantile( p, alpha, beta );
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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 ) );
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}

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