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README.md |
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
.
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
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/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 ) );
}