Logarithm of Cumulative Distribution Function
Logistic distribution logarithm of cumulative distribution function.
The cumulative distribution function for a logistic random variable is
where mu
is the location parameter and s > 0
is the scale parameter.
Usage
var logcdf = require( '@stdlib/stats/base/dists/logistic/logcdf' );
logcdf( x, mu, s )
Evaluates the logarithm of the cumulative distribution function (CDF) for a logistic distribution with parameters mu
(location parameter) and s
(scale parameter).
var y = logcdf( 2.0, 0.0, 1.0 );
// returns ~-0.127
y = logcdf( 0.0, 0.0, 1.0 );
// returns ~-0.693
y = logcdf( -1.0, 4.0, 2.0 );
// returns ~-2.579
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 s < 0
, the function returns NaN
.
var y = logcdf( 2.0, 0.0, -1.0 );
// returns NaN
If provided s = 0
, the function evaluates the logarithm of the CDF of a degenerate distribution centered at mu
.
var y = logcdf( 2.0, 8.0, 0.0 );
// returns -Infinity
y = logcdf( 8.0, 8.0, 0.0 );
// returns 0.0
y = logcdf( 10.0, 8.0, 0.0 );
// returns 0.0
logcdf.factory( mu, s )
Returns a function for evaluating the logarithm of the cumulative distribution function of a logistic distribution with parameters mu
(location parameter) and s
(scale parameter).
var mylogcdf = logcdf.factory( 10.0, 2.0 );
var y = mylogcdf( 10.0 );
// returns ~-0.693
y = mylogcdf( 8.0 );
// returns ~-1.313
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/logistic/logcdf' );
var mu;
var s;
var x;
var y;
var i;
for ( i = 0; i < 10; i++ ) {
x = randu() * 10.0;
mu = randu() * 10.0;
s = randu() * 10.0;
y = logcdf( x, mu, s );
console.log( 'x: %d, µ: %d, s: %d, ln(F(x;µ,s)): %d', x, mu, s, y );
}