@stdlib/stats-base-dists-kumaraswamy-cdf
v0.2.2
Published
Kumaraswamy's double bounded distribution cumulative distribution function (CDF).
Downloads
132,523
Readme
Cumulative Distribution Function
Kumaraswamy's double bounded distribution cumulative distribution function.
The cumulative distribution function for a Kumaraswamy's double bounded random variable is
where a > 0
is the first shape parameter and b > 0
is the second shape parameter.
Installation
npm install @stdlib/stats-base-dists-kumaraswamy-cdf
Usage
var cdf = require( '@stdlib/stats-base-dists-kumaraswamy-cdf' );
cdf( x, a, b )
Evaluates the cumulative distribution function (CDF) for a Kumaraswamy's double bounded distribution with parameters a
(first shape parameter) and b
(second shape parameter).
var y = cdf( 0.5, 1.0, 1.0 );
// returns 0.5
y = cdf( 0.5, 2.0, 4.0 );
// returns ~0.684
y = cdf( 0.2, 2.0, 2.0 );
// returns ~0.078
y = cdf( 0.8, 4.0, 4.0 );
// returns ~0.878
y = cdf( -0.5, 4.0, 2.0 );
// returns 0.0
y = cdf( -Infinity, 4.0, 2.0 );
// returns 0.0
y = cdf( 1.5, 4.0, 2.0 );
// returns 1.0
y = cdf( +Infinity, 4.0, 2.0 );
// returns 1.0
If provided NaN
as any argument, the function returns NaN
.
var y = cdf( NaN, 1.0, 1.0 );
// returns NaN
y = cdf( 0.0, NaN, 1.0 );
// returns NaN
y = cdf( 0.0, 1.0, NaN );
// returns NaN
If provided a <= 0
, the function returns NaN
.
var y = cdf( 2.0, -1.0, 0.5 );
// returns NaN
y = cdf( 2.0, 0.0, 0.5 );
// returns NaN
If provided b <= 0
, the function returns NaN
.
var y = cdf( 2.0, 0.5, -1.0 );
// returns NaN
y = cdf( 2.0, 0.5, 0.0 );
// returns NaN
cdf.factory( a, b )
Returns a function for evaluating the cumulative distribution function for a Kumaraswamy's double bounded distribution with parameters a
(first shape parameter) and b
(second shape parameter).
var mycdf = cdf.factory( 0.5, 0.5 );
var y = mycdf( 0.8 );
// returns ~0.675
y = mycdf( 0.3 );
// returns ~0.327
Examples
var randu = require( '@stdlib/random-base-randu' );
var EPS = require( '@stdlib/constants-float64-eps' );
var cdf = require( '@stdlib/stats-base-dists-kumaraswamy-cdf' );
var a;
var b;
var x;
var y;
var i;
for ( i = 0; i < 10; i++ ) {
x = randu();
a = ( randu()*5.0 ) + EPS;
b = ( randu()*5.0 ) + EPS;
y = cdf( x, a, b );
console.log( 'x: %d, a: %d, b: %d, F(x;a,b): %d', x.toFixed( 4 ), a.toFixed( 4 ), b.toFixed( 4 ), y.toFixed( 4 ) );
}
Notice
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.
Community
License
See LICENSE.
Copyright
Copyright © 2016-2024. The Stdlib Authors.