@stdlib/stats-base-dists-triangular-variance
v0.3.1TypeScript
Triangular distribution variance.
0/weekUpdated 4 days agoApache-2.0Unpacked: 46.3 KB
Published by The Stdlib Authors
npm install @stdlib/stats-base-dists-triangular-varianceWe 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. The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases. When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there. To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
About stdlib...
Variance
[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url]
> [Triangular][triangular-distribution] distribution [variance][variance].
The [variance][variance] 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-variance
Usage
`javascript`
var variance = require( '@stdlib/stats-base-dists-triangular-variance' );
#### variance( a, b, c )
Returns the [variance][variance] of a [triangular][triangular-distribution] distribution with minimum support a, maximum support b, and mode c.
`javascript
var v = variance( 0.0, 1.0, 0.8 );
// returns ~0.047
v = variance( 4.0, 12.0, 5.0 );
// returns ~3.167
v = variance( 2.0, 8.0, 5.0 );
// returns 1.5
`
If provided NaN as any argument, the function returns NaN.
`javascript
var v = variance( NaN, 4.0, 2.0 );
// returns NaN
v = variance( 0.0, NaN, 2.0 );
// returns NaN
v = variance( 0.0, 4.0, NaN );
// returns NaN
`
If provided parameters not satisfying a <= c <= b, the function returns NaN.
`javascript
var y = variance( 1.0, 0.0, 1.5 );
// returns NaN
y = variance( 0.0, 1.0, -1.0 );
// returns NaN
y = variance( 0.0, -1.0, 0.5 );
// returns NaN
`
Examples
`javascript
var randu = require( '@stdlib/random-base-randu' );
var variance = require( '@stdlib/stats-base-dists-triangular-variance' );
var a;
var b;
var c;
var v;
var i;
for ( i = 0; i < 10; i++ ) {
a = ( randu()*10.0 );
b = ( randu()*10.0 ) + a;
c = ( randu()*( b-a ) ) + a;
v = variance( a, b, c );
console.log( 'a: %d, b: %d, c: %d, Var(X;a,b,c): %d', a.toFixed( 4 ), b.toFixed( 4 ), c.toFixed( 4 ), v.toFixed( 4 ) );
}
`
*
C APIs
$3
`c`
#include "stdlib/stats/base/dists/triangular/variance.h"
#### stdlib_base_dists_triangular_variance( a, b, c )
Returns the [variance][variance] of a [triangular][triangular-distribution] distribution with minimum support a, maximum support b, and mode c.
`c`
double out = stdlib_base_dists_triangular_variance( 0.0, 1.0, 0.5 );
// returns ~0.056
The function accepts the following arguments:
- a: [in] double minimum support.[in] double
- b: maximum support.[in] double
- c: mode.
`c`
double stdlib_base_dists_triangular_variance( const double a, const double b, const double c );
$3
`c
#include "stdlib/stats/base/dists/triangular/variance.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 y;
int i;
for ( i = 0; i < 25; i++ ) {
a = random_uniform( 0.0, 10.0 );
b = random_uniform( a, a+10.0 );
c = random_uniform( a, b );
y = stdlib_base_dists_triangular_variance( a, b, c );
printf( "a: %lf, b: %lf, c: %lf, Var(X;a,b,c): %lf\n", a, b, c, y );
}
}
`
*
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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[umd]: https://github.com/umdjs/umd
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[deno-url]: https://github.com/stdlib-js/stats-base-dists-triangular-variance/tree/deno
[deno-readme]: https://github.com/stdlib-js/stats-base-dists-triangular-variance/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/stats-base-dists-triangular-variance/tree/umd
[umd-readme]: https://github.com/stdlib-js/stats-base-dists-triangular-variance/blob/umd/README.md
[esm-url]: https://github.com/stdlib-js/stats-base-dists-triangular-variance/tree/esm
[esm-readme]: https://github.com/stdlib-js/stats-base-dists-triangular-variance/blob/esm/README.md
[branches-url]: https://github.com/stdlib-js/stats-base-dists-triangular-variance/blob/main/branches.md
[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-base-dists-triangular-variance/main/LICENSE
[triangular-distribution]: https://en.wikipedia.org/wiki/Triangular_distribution
[variance]: https://en.wikipedia.org/wiki/Variance