@stdlib/stats-base-dists-gumbel-cdf

Gumbel distribution cumulative distribution function (CDF).

Usage no npm install needed!

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README

Cumulative Distribution Function

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Gumbel distribution cumulative distribution function.

The cumulative distribution function for a Gumbel random variable is

Cumulative distribution function for a Gumbel distribution.

where mu is the location parameter and beta > 0 is the scale parameter.

Installation

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

Usage

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

cdf( x, mu, beta )

Evaluates the cumulative distribution function (CDF) for a Gumbel distribution with parameters mu (location parameter) and beta (scale parameter).

var y = cdf( 10.0, 0.0, 3.0 );
// returns ~0.965

y = cdf( -2.0, 0.0, 3.0 );
// returns ~0.143

y = cdf( 0.0, 0.0, 1.0 );
// returns ~0.368

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

var y = cdf( NaN, 0.0, 1.0 );
// returns NaN

y = cdf( 0.0, NaN, 1.0 );
// returns NaN

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

If provided beta <= 0, the function returns NaN.

var y = cdf( 2.0, 0.0, -1.0 );
// returns NaN

y = cdf( 2.0, 0.0, 0.0 );
// returns NaN

cdf.factory( mu, beta )

Returns a function for evaluating the cumulative distribution function of a Gumbel distribution with parameters mu (location parameter) and beta (scale parameter).

var mycdf = cdf.factory( 0.0, 3.0 );

var y = mycdf( 10.0 );
// returns ~0.965

y = mycdf( -2.0 );
// returns ~0.143

Examples

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

var beta;
var mu;
var x;
var y;
var i;

for ( i = 0; i < 100; i++ ) {
    x = randu() * 10.0;
    mu = randu() * 10.0;
    beta = randu() * 10.0;
    y = cdf( x, mu, beta );
    console.log( 'x: %d, µ: %d, β: %d, F(x;µ,β): %d', x.toFixed( 4 ), mu.toFixed( 4 ), beta.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.

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License

See LICENSE.

Copyright

Copyright © 2016-2022. The Stdlib Authors.