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README.md |
Logarithm of Probability Density Function
Fréchet distribution logarithm of probability density function.
The probability density function for a Fréchet random variable is
where α > 0
is the shape, s > 0
the scale and m
the location parameter.
Usage
var logpdf = require( '@stdlib/stats/base/dists/frechet/logpdf' );
logpdf( x, alpha, s, m )
Evaluates the logarithm of the probability density function (PDF) for a Fréchet distribution with shape alpha
, scale s
, and location m
at a value x
.
var y = logpdf( 10.0, 2.0, 3.0, 5.0 );
// returns ~-2.298
y = logpdf( -3.0, 1.0, 2.0, -4.0 );
// returns ~-1.307
y = logpdf( 0.0, 2.0, 1.0, -1.0 );
// returns ~-0.307
If provided x <= m
, the function returns -Infinity
.
y = logpdf( -2.0, 2.0, 1.0, -1.0 );
// returns -Infinity
If provided NaN
as any argument, the function returns NaN
.
var y = logpdf( NaN, 1.0, 1.0, 0.0 );
// returns NaN
y = logpdf( 0.0, NaN, 1.0, 0.0 );
// returns NaN
y = logpdf( 0.0, 1.0, NaN, 0.0);
// returns NaN
y = logpdf( 0.0, 1.0, 1.0, NaN );
// returns NaN
If provided alpha <= 0
, the function returns NaN
.
var y = logpdf( 2.0, -0.1, 1.0, 1.0 );
// returns NaN
y = logpdf( 2.0, 0.0, 1.0, 1.0 );
// returns NaN
If provided s <= 0
, the function returns NaN
.
var y = logpdf( 2.0, 1.0, -1.0, 1.0 );
// returns NaN
y = logpdf( 2.0, 1.0, 0.0, 1.0 );
// returns NaN
logpdf.factory( alpha, s, m )
Returns a function for evaluating the logarithm of the probability density function of a Fréchet distribution with shape alpha
, scale s
, and location m
.
var mylogpdf = logpdf.factory( 3.0, 3.0, 5.0 );
var y = mylogpdf( 10.0 );
// returns ~-2.259
y = mylogpdf( 7.0 );
// returns ~-1.753
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 logpdf = require( '@stdlib/stats/base/dists/frechet/logpdf' );
var alpha;
var m;
var s;
var x;
var y;
var i;
for ( i = 0; i < 100; i++ ) {
alpha = randu() * 10.0;
x = randu() * 10.0;
s = randu() * 10.0;
m = randu() * 10.0;
y = logpdf( x, alpha, s, m );
console.log( 'x: %d, α: %d, s: %d, m: %d, ln(f(x;α,s,m)): %d', x.toFixed( 4 ), alpha.toFixed( 4 ), s.toFixed( 4 ), m.toFixed( 4 ), y.toFixed( 4 ) );
}