Logarithm of Cumulative Distribution Function

Uniform distribution logarithm of cumulative distribution function.

The cumulative distribution function for a continuous uniform 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-uniform-logcdf

Usage

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

logcdf( x, a, b )

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

var y = logcdf( 9.0, 0.0, 10.0 );
// returns ~-0.105

y = logcdf( 0.5, 0.0, 2.0 );
// returns ~-1.386

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 a uniform distribution with parameters a (minimum support) and b (maximum support).

var mylogcdf = logcdf.factory( 0.0, 10.0 );
var y = mylogcdf( 0.5 );
// returns ~-2.996

y = mylogcdf( 8.0 );
// returns ~-0.223

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-uniform-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 ) );
}

C APIs

Usage

#include "stdlib/stats/base/dists/uniform/logcdf.h"

stdlib_base_dists_uniform_logcdf( x, a, b )

Evaluates the logarithm of the cumulative distribution function of a uniform distribution with parameters a (minimum support) and b (maximum support).

double out = stdlib_base_dists_uniform_logcdf( 9.0, 0.0, 10.0 );
// returns ~-0.105

The function accepts the following arguments:

• x: [in] double input value.
• a: [in] double minimum support.
• b: [in] double maximum support.

double stdlib_base_dists_uniform_logcdf( const double x, const double a, const double b );

Examples

#include "stdlib/stats/base/dists/uniform/logcdf.h"
#include <stdlib.h>
#include <stdio.h>

static double random_uniform( const double min, const double max ) {
    double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
    return min + ( v*(max-min) );
}

int main( void ) {
    double a;
    double b;
    double x;
    double y;
    int i;

    for ( i = 0; i < 25; i++ ) {
        x = random_uniform( -10.0, 10.0 );
        a = random_uniform( -20.0, 0.0 );
        b = random_uniform( a, a+40.0 );
        y = stdlib_base_dists_uniform_logcdf( x, a, b );
        printf( "x: %lf, a: %lf, b: %lf, ln(F(x;a,b)): %lf\n", x, a, b, y );
    }
}

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 © 2016-2026. The Stdlib Authors.