Cumulative Distribution Function

Geometric distribution cumulative distribution function.

The cumulative distribution function for a geometric random variable is

where 0 <= p <= 1 is the success probability. x denotes the number of failures before the first success.

Installation

npm install @stdlib/stats-base-dists-geometric-cdf

Usage

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

cdf( x, p )

Evaluates the cumulative distribution function for a geometric distribution with success probability p.

var y = cdf( 2.0, 0.5 );
// returns 0.875

y = cdf( 2.0, 0.1 );
// returns ~0.271

If provided NaN as any argument, the function returns NaN.

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

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

If provided a success probability p outside of [0,1], the function returns NaN.

var y = cdf( 2.0, -1.0 );
// returns NaN

y = cdf( 2.0, 1.5 );
// returns NaN

cdf.factory( p )

Returns a function for evaluating the cumulative distribution function of a geometric distribution with success probability p

var mycdf = cdf.factory( 0.5 );
var y = mycdf( 3.0 );
// returns 0.9375

y = mycdf( 1.0 );
// returns 0.75

Examples

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

var p;
var x;
var y;
var i;

for ( i = 0; i < 10; i++ ) {
    x = randu() * 5.0;
    p = randu();
    y = cdf( x, p );
    console.log( 'x: %d, p: %d, F(x;p): %d', x.toFixed( 4 ), p.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

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