@stdlib/stats-base-dists-triangular-quantile
v0.3.1TypeScript
Triangular distribution quantile function.
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Published by The Stdlib Authors
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Quantile Function
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> [Triangular][triangular-distribution] distribution [quantile function][quantile-function].
The [quantile function][quantile-function] for a [Triangular][triangular-distribution] random variable is
where a is the lower limit, b is the upper limit and c is the mode.
Installation
``bash`
npm install @stdlib/stats-base-dists-triangular-quantile
Usage
`javascript`
var quantile = require( '@stdlib/stats-base-dists-triangular-quantile' );
#### quantile( p, a, b, c )
Evaluates the [quantile function][quantile-function] for a [triangular][triangular-distribution] distribution with parameters a (lower limit), b (upper limit) and c (mode).
`javascript
var y = quantile( 0.9, -1.0, 1.0, 0.0 );
// returns ~0.553
y = quantile( 0.1, -1.0, 1.0, 0.5 );
// returns ~-0.452
y = quantile( 0.1, -20.0, 0.0, -2.0 );
// returns -14.0
y = quantile( 0.8, 0.0, 20.0, 0.0 );
// returns ~11.056
`
If provided a probability p outside the interval [0,1], the function returns NaN.
`javascript
var y = quantile( 1.9, 0.0, 1.0, 0.5 );
// returns NaN
y = quantile( -0.1, 0.0, 1.0, 0.5 );
// returns NaN
`
If provided NaN as any argument, the function returns NaN.
`javascript
var y = quantile( NaN, 0.0, 1.0, 0.5 );
// returns NaN
y = quantile( 0.1, NaN, 1.0, 0.5 );
// returns NaN
y = quantile( 0.1, 0.0, NaN, 0.5 );
// returns NaN
y = quantile( 0.1, 0.0, 1.0, NaN );
// returns NaN
`
If provided parameters not satisfying a <= c <= b, the function returns NaN.
`javascript
var y = quantile( 0.1, 1.0, 0.0, 1.5 );
// returns NaN
y = quantile( 0.1, 1.0, 0.0, -1.0 );
// returns NaN
y = quantile( 0.1, 0.0, -1.0, 0.5 );
// returns NaN
`
#### quantile.factory( a, b, c )
Returns a function for evaluating the [quantile function][quantile-function] of a [triangular][triangular-distribution] distribution with parameters a (lower limit), b (upper limit) and c (mode).
`javascript
var myquantile = quantile.factory( 2.0, 4.0, 2.5 );
var y = myquantile( 0.4 );
// returns ~2.658
y = myquantile( 0.8 );
// returns ~3.225
`
Examples
`javascript
var randu = require( '@stdlib/random-base-randu' );
var quantile = require( '@stdlib/stats-base-dists-triangular-quantile' );
var a;
var b;
var c;
var p;
var y;
var i;
for ( i = 0; i < 25; i++ ) {
p = randu();
a = randu() * 10.0;
b = a + (randu() * 40.0);
c = a + ((b-a) * randu());
y = quantile( p, a, b, c );
console.log( 'p: %d, a: %d, b: %d, c: %d, Q(p;a,b,c): %d', p.toFixed( 4 ), a.toFixed( 4 ), b.toFixed( 4 ), c.toFixed( 4 ), y.toFixed( 4 ) );
}
`
*
C APIs
$3
`c`
#include "stdlib/stats/base/dists/triangular/quantile.h"
#### stdlib_base_dists_triangular_quantile( p, a, b, c )
Evaluates the [quantile function][quantile-function] for a [triangular][triangular-distribution] distribution with parameters a (lower limit), b (upper limit), and c (mode).
`c`
double out = stdlib_base_dists_triangular_quantile( 0.9, -1.0, 1.0, 0.0 );
// returns ~0.553
The function accepts the following arguments:
- p: [in] double input probability.[in] double
- a: minimum support.[in] double
- b: maximum support.[in] double
- c: mode.
`c`
double stdlib_base_dists_triangular_quantile( const double p, const double a, const double b, const double c );
$3
`c
#include "stdlib/stats/base/dists/triangular/quantile.h"
#include
#include
static double random_uniform( const double min, const double max ) {
double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
return min + ( v*(max-min) );
}
int main( void ) {
double a;
double b;
double c;
double p;
double v;
int i;
for ( i = 0; i < 25; i++ ) {
p = random_uniform( 0.0, 1.0 );
a = random_uniform( 0.0, 10.0 );
b = random_uniform( a, a+10.0 );
c = random_uniform( a, b );
v = stdlib_base_dists_triangular_quantile( p, a, b, c );
printf( "p: %lf, a: %lf, b: %lf, c: %lf, Q(p;a,b,c): %lf\n", p, a, b, c, v );
}
}
`
*
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].
#### Community
[![Chat][chat-image]][chat-url]
---
License
See [LICENSE][stdlib-license].
Copyright
Copyright © 2016-2026. The Stdlib [Authors][stdlib-authors].
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[deno-readme]: https://github.com/stdlib-js/stats-base-dists-triangular-quantile/blob/deno/README.md
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[esm-url]: https://github.com/stdlib-js/stats-base-dists-triangular-quantile/tree/esm
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[branches-url]: https://github.com/stdlib-js/stats-base-dists-triangular-quantile/blob/main/branches.md
[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-base-dists-triangular-quantile/main/LICENSE
[triangular-distribution]: https://en.wikipedia.org/wiki/Triangular_distribution
[quantile-function]: https://en.wikipedia.org/wiki/Quantile_function