# 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.

## 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 ) );
}