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Triangular distribution cumulative distribution function.
The cumulative distribution function for a triangular random variable is
where a
is the lower limit, b
is the upper limit, and c
is the mode.
npm install @stdlib/stats-base-dists-triangular-cdf
var cdf = require( '@stdlib/stats-base-dists-triangular-cdf' );
Evaluates the cumulative distribution function (CDF) for a triangular distribution with parameters a
(lower limit), b
(upper limit) and c
(mode).
var y = cdf( 0.5, -1.0, 1.0, 0.0 );
// returns 0.875
y = cdf( 0.5, -1.0, 1.0, 0.5 );
// returns 0.75
y = cdf( -10.0, -20.0, 0.0, -2.0 );
// returns ~0.278
y = cdf( -2.0, -1.0, 1.0, 0.0 );
// returns 0.0
If provided NaN
as any argument, the function returns NaN
.
var y = cdf( NaN, 0.0, 1.0, 0.5 );
// returns NaN
y = cdf( 0.0, NaN, 1.0, 0.5 );
// returns NaN
y = cdf( 0.0, 0.0, NaN, 0.5 );
// returns NaN
y = cdf( 2.0, 1.0, 0.0, NaN );
// returns NaN
If provided parameters not satisfying a <= c <= b
, the function returns NaN
.
var y = cdf( 2.0, 1.0, 0.0, 1.5 );
// returns NaN
y = cdf( 2.0, 1.0, 0.0, -1.0 );
// returns NaN
y = cdf( 2.0, 0.0, -1.0, 0.5 );
// returns NaN
Returns a function for evaluating the cumulative distribution function of a triangular distribution with parameters a
(lower limit), b
(upper limit) and c
(mode).
var mycdf = cdf.factory( 0.0, 10.0, 2.0 );
var y = mycdf( 0.5 );
// returns 0.0125
y = mycdf( 8.0 );
// returns 0.95
var randu = require( '@stdlib/random-base-randu' );
var cdf = require( '@stdlib/stats-base-dists-triangular-cdf' );
var a;
var b;
var c;
var x;
var y;
var i;
for ( i = 0; i < 25; i++ ) {
x = randu() * 30.0;
a = randu() * 10.0;
b = a + (randu() * 40.0);
c = a + ((b-a) * randu());
y = cdf( x, a, b, c );
console.log( 'x: %d, a: %d, b: %d, c: %d, F(x;a,b,c): %d', x.toFixed( 4 ), a.toFixed( 4 ), b.toFixed( 4 ), c.toFixed( 4 ), y.toFixed( 4 ) );
}
This package is part of 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, see the main project repository.
See LICENSE.
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