@stdlib/stats-base-dists-arcsine-logcdf NPM

Logarithm of Cumulative Distribution Function

Arcsine distribution logarithm of cumulative distribution function.

The cumulative distribution function for an arcsine random variable is

where a is the minimum support and b is the maximum support. The parameters must satisfy a < b.

Installation

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

Usage

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

logcdf( x, a, b )

Evaluates the logarithm of the cumulative distribution function (CDF) for an arcsine distribution with parameters a (minimum support) and b (maximum support).

var y = logcdf( 9.0, 0.0, 10.0 );
// returns ~-0.23

y = logcdf( 0.5, 0.0, 2.0 );
// returns ~-1.1

y = logcdf( -Infinity, 2.0, 4.0 );
// returns -Infinity

y = logcdf( +Infinity, 2.0, 4.0 );
// returns 0.0

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 a >= b, the function returns NaN.

var y = logcdf( 1.0, 2.5, 2.0 );
// returns NaN

logcdf.factory( a, b )

Returns a function for evaluating the logarithm of the cumulative distribution function of an arcsine distribution with parameters a (minimum support) and b (maximum support).

var mylogcdf = logcdf.factory( 0.0, 10.0 );
var y = mylogcdf( 0.5 );
// returns ~-1.941

y = mylogcdf( 8.0 );
// returns ~-0.35

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-arcsine-logcdf' );

var a;
var b;
var x;
var y;
var i;

for ( i = 0; i < 25; i++ ) {
    x = ( randu()*20.0 ) - 10.0;
    a = ( randu()*20.0 ) - 20.0;
    b = a + ( randu()*40.0 );
    y = logcdf( x, a, b );
    console.log( 'x: %d, a: %d, b: %d, ln(F(x;a,b)): %d', x.toFixed( 4 ), a.toFixed( 4 ), b.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.