@stdlib/stats-base-dists-discrete-uniform-cdf

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Cumulative Distribution Function

Discrete uniform distribution cumulative distribution function.

The cumulative distribution function for a discrete uniform random variable is

where a is the minimum support and b is the maximum support. The parameters must satisfy a <= b.

Installation

npm install @stdlib/stats-base-dists-discrete-uniform-cdf

Usage

var cdf = require( '@stdlib/stats-base-dists-discrete-uniform-cdf' );

cdf( x, a, b )

Evaluates the cumulative distribution function (CDF) for a discrete uniform distribution with parameters a (minimum support) and b (maximum support).

var y = cdf( 9.0, 0, 10 );
// returns ~0.909

y = cdf( 0.5, -2, 2 );
// returns ~0.6

y = cdf( -Infinity, 2, 4 );
// returns 0.0

y = cdf( Infinity, 2, 4 );
// returns 1.0

If a or b is not an integer value, the function returns NaN.

var y = cdf( 0.2, 1, 5.5 );
// returns NaN

y = cdf( NaN, 0, 1 );
// returns NaN

y = cdf( 0.0, NaN, 1 );
// returns NaN

y = cdf( 0.0, 0, NaN );
// returns NaN

If provided a > b, the function returns NaN.

var y = cdf( 0.5, 3, 2);
// returns NaN

cdf.factory( a, b )

Returns a function for evaluating the cumulative distribution function of a discrete uniform distribution with parameters a (minimum support) and b (maximum support).

var mycdf = cdf.factory( 0, 10 );
var y = mycdf( 0.5 );
// returns ~0.091

y = mycdf( 8.0 );
// returns ~0.818

Examples

var randint = require( '@stdlib/random-base-discrete-uniform' );
var randu = require( '@stdlib/random-base-randu' );
var cdf = require( '@stdlib/stats-base-dists-discrete-uniform-cdf' );

var randa = randint.factory( 0, 10 );
var randb = randint.factory();
var a;
var b;
var x;
var v;
var i;

for ( i = 0; i < 10; i++ ) {
    x = randu() * 15.0;
    a = randa();
    b = randb( a, a+randa() );
    v = 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 ), v.toFixed( 4 ) );
}

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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

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License

See LICENSE.

Copyright

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