@stdlib/stats-base-dists-gumbel-logcdf
v0.2.2
Published
Gumbel distribution logarithm of cumulative distribution function.
Downloads
274
Readme
Logarithm of Cumulative Distribution Function
Gumbel distribution logarithm of cumulative distribution function.
The cumulative distribution function for a Gumbel random variable is
where mu
is the location parameter and beta > 0
is the scale parameter.
Installation
npm install @stdlib/stats-base-dists-gumbel-logcdf
Usage
var logcdf = require( '@stdlib/stats-base-dists-gumbel-logcdf' );
logcdf( x, mu, beta )
Evaluates the logarithm of the cumulative distribution function (CDF) for a Gumbel distribution with parameters mu
(location parameter) and beta
(scale parameter).
var y = logcdf( 10.0, 0.0, 3.0 );
// returns ~-0.036
y = logcdf( -2.0, 0.0, 3.0 );
// returns ~-1.948
y = logcdf( 0.0, 0.0, 1.0 );
// returns ~-1
If provided NaN
as any argument, the function returns NaN
.
var y = logcdf( NaN, 0.0, 1.0 );
// returns NaN
y = logcdf( 0.0, NaN, 1.0 );
// returns NaN
y = logcdf( 0.0, 0.0, NaN );
// returns NaN
If provided beta <= 0
, the function returns NaN
.
var y = logcdf( 2.0, 0.0, -1.0 );
// returns NaN
y = logcdf( 2.0, 0.0, 0.0 );
// returns NaN
logcdf.factory( mu, beta )
Returns a function for evaluating the logarithm of the cumulative distribution function of a Gumbel distribution with parameters mu
(location parameter) and beta
(scale parameter).
var mylogcdf = logcdf.factory( 0.0, 3.0 );
var y = mylogcdf( 10.0 );
// returns ~-0.036
y = mylogcdf( -2.0 );
// returns ~-1.948
Notes
- In virtually all cases, using the
logpdf
orlogcdf
functions is preferable to manually computing the logarithm of thepdf
orcdf
, respectively, since the latter is prone to overflow and underflow.
Examples
var randu = require( '@stdlib/random-base-randu' );
var logcdf = require( '@stdlib/stats-base-dists-gumbel-logcdf' );
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 = logcdf( x, mu, beta );
console.log( 'x: %d, µ: %d, β: %d, ln(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.
Community
License
See LICENSE.
Copyright
Copyright © 2016-2024. The Stdlib Authors.