Logarithm of Probability Density Function
Evaluate the natural logarithm of the probability density function (PDF) for an Erlang distribution.
The probability density function (PDF) for an Erlang random variable is
where k
is the shape parameter and lambda
is the rate parameter.
Usage
var logpdf = require( '@stdlib/stats/base/dists/erlang/logpdf' );
logpdf( x, k, lambda )
Evaluates the natural logarithm of the probability density function (PDF) for an Erlang distribution with parameters k
(shape parameter) and lambda
(rate parameter).
var y = logpdf( 0.1, 1, 1.0 );
// returns ~-0.1
y = logpdf( 0.5, 2, 2.5 );
// returns ~-0.111
y = logpdf( -1.0, 4, 2.0 );
// returns -Infinity
If provided NaN
as any argument, the function returns NaN
.
var y = logpdf( NaN, 1, 1.0 );
// returns NaN
y = logpdf( 0.0, NaN, 1.0 );
// returns NaN
y = logpdf( 0.0, 1, NaN );
// returns NaN
If not provided a nonnegative integer for k
, the function returns NaN
.
var y = logpdf( 2.0, -2, 0.5 );
// returns NaN
y = logpdf( 2.0, 0.5, 0.5 );
// returns NaN
If provided k = 0
, the function evaluates the logarithm of the PDF of a degenerate distribution centered at 0
.
var y = logpdf( 2.0, 0.0, 2.0 );
// returns -Infinity
y = logpdf( 0.0, 0.0, 2.0 );
// returns Infinity
If provided lambda <= 0
, the function returns NaN
.
var y = logpdf( 2.0, 1, 0.0 );
// returns NaN
y = logpdf( 2.0, 1, -1.0 );
// returns NaN
logpdf.factory( k, lambda )
Returns a function
for evaluating the PDF for an Erlang distribution with parameters k
(shape parameter) and lambda
(rate parameter).
var mylogpdf = logpdf.factory( 3, 1.5 );
var y = mylogpdf( 1.0 );
// returns ~-0.977
y = mylogpdf( 4.0 );
// returns ~-2.704
Examples
var randu = require( '@stdlib/random/base/randu' );
var round = require( '@stdlib/math/base/special/round' );
var logpdf = require( '@stdlib/stats/base/dists/erlang/logpdf' );
var lambda;
var k;
var x;
var y;
var i;
for ( i = 0; i < 20; i++ ) {
x = randu() * 10.0;
k = round( randu() * 10.0 );
lambda = randu() * 5.0;
y = logpdf( x, k, lambda );
console.log( 'x: %d, k: %d, λ: %d, ln(f(x;k,λ)): %d', x.toFixed( 4 ), k, lambda.toFixed( 4 ), y.toFixed( 4 ) );
}