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README.md |
Logarithm of Cumulative Distribution Function
Lévy distribution logarithm of cumulative distribution function.
The cumulative distribution function for a Lévy random variable is
where mu
is the location parameter and b > 0
is the scale parameter.
Usage
var logcdf = require( '@stdlib/stats/base/dists/levy/logcdf' );
logcdf( x, mu, c )
Evaluates the logarithm of the cumulative distribution function (CDF) for a Lévy distribution with parameters mu
(location parameter) and c > 0
(scale parameter).
var y = logcdf( 2.0, 0.0, 1.0 );
// returns ~-0.735
y = logcdf( 12.0, 10.0, 3.0 );
// returns ~-1.51
y = logcdf( 9.0, 10.0, 3.0 );
// returns -Infinity
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 c <= 0
, the function returns NaN
.
var y = logcdf( 2.0, 0.0, -1.0 );
// returns NaN
y = logcdf( 2.0, 0.0, 0.0 );
// returns NaN
logcdf.factory( mu, c )
Returns a function for evaluating the logarithm of the cumulative distribution function of a Lévy distribution with parameters mu
(location parameter) and c > 0
(scale parameter).
var mylogcdf = logcdf.factory( 3.0, 1.5 );
var y = mylogcdf( 4.0 );
// returns ~-1.511
y = mylogcdf( 2.0 );
// returns -Infinity
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 EPS = require( '@stdlib/constants/float64/eps' );
var logcdf = require( '@stdlib/stats/base/dists/levy/logcdf' );
var mu;
var c;
var x;
var y;
var i;
for ( i = 0; i < 100; i++ ) {
mu = randu() * 10.0;
x = ( randu()*10.0 ) + mu;
c = ( randu()*10.0 ) + EPS;
y = logcdf( x, mu, c );
console.log( 'x: %d, µ: %d, c: %d, ln(F(x;µ,c)): %d', x.toFixed( 4 ), mu.toFixed( 4 ), c.toFixed( 4 ), y.toFixed( 4 ) );
}