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

Lévy distribution cumulative distribution function (CDF).

Usage no npm install needed!

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README

Cumulative Distribution Function

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Lévy distribution cumulative distribution function.

The cumulative distribution function for a Lévy random variable is

Cumulative distribution function for a Lévy distribution.

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

Installation

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

Usage

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

cdf( x, mu, c )

Evaluates the cumulative distribution function (CDF) for a Lévy distribution with parameters mu (location parameter) and c > 0 (scale parameter).

var y = cdf( 2.0, 0.0, 1.0 );
// returns ~0.48

y = cdf( 12.0, 10.0, 3.0 );
// returns ~0.221

y = cdf( 9.0, 10.0, 3.0 );
// returns 0.0

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 c <= 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, c )

Returns a function for evaluating the cumulative distribution function of a Lévy distribution with parameters mu (location parameter) and c > 0 (scale parameter).

var mycdf = cdf.factory( 3.0, 1.5 );

var y = mycdf( 4.0 );
// returns ~0.22

y = mycdf( 2.0 );
// returns 0.0

Examples

var randu = require( '@stdlib/random-base-randu' );
var EPS = require( '@stdlib/constants-float64-eps' );
var cdf = require( '@stdlib/stats-base-dists-levy-cdf' );

var mu;
var c;
var x;
var y;
var i;

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