0.2.1 • Published 2 months ago

@stdlib/stats-base-dists-rayleigh-logcdf v0.2.1

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Repository
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Last release
2 months ago

Logarithm of Cumulative Distribution Function

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Rayleigh distribution logarithm of cumulative distribution function.

The cumulative distribution function for a Rayleigh random variable is

where sigma > 0 is the scale parameter.

Installation

npm install @stdlib/stats-base-dists-rayleigh-logcdf

Usage

var logcdf = require( '@stdlib/stats-base-dists-rayleigh-logcdf' );

logcdf( x, sigma )

Evaluates the logarithm of the cumulative distribution function for a Rayleigh distribution with scale parameter sigma.

var y = logcdf( 2.0, 3.0 );
// returns ~-1.613

y = logcdf( 1.0, 2.0 );
// returns ~-2.141

y = logcdf( -1.0, 4.0 );
// returns -Infinity

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

var y = logcdf( NaN, 1.0 );
// returns NaN

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

If provided sigma < 0, the function returns NaN.

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

If provided sigma = 0, the function evaluates the logarithm of the CDF for a degenerate distribution centered at 0.

var y = logcdf( -2.0, 0.0 );
// returns -Infinity

y = logcdf( 0.0, 0.0 );
// returns 0.0

y = logcdf( 2.0, 0.0 );
// returns 0.0

logcdf.factory( sigma )

Returns a function for evaluating the logarithm of the cumulative distribution function of a Rayleigh distribution with parameter sigma (scale parameter).

var mylogCDF = logcdf.factory( 0.5 );
y = mylogCDF( 1.0 );
// returns ~-0.145

y = mylogCDF( 0.5 );
// returns ~-0.933

Notes

  • In virtually all cases, using the logpdf or logcdf functions is preferable to manually computing the logarithm of the pdf or cdf, 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-rayleigh-logcdf' );

var sigma;
var x;
var y;
var i;

for ( i = 0; i < 10; i++ ) {
    x = randu() * 10.0;
    sigma = randu() * 10.0;
    y = logcdf( x, sigma );
    console.log( 'x: %d, σ: %d, log(F(x;σ)): %d', x.toFixed( 4 ), sigma.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 © 2016-2024. The Stdlib Authors.