# Logarithm of Probability Density Function

Evaluate the natural logarithm of the probability density function for a Kumaraswamy's double bounded distribution.

The probability density function (PDF) for a Kumaraswamy's double bounded random variable is

where a > 0 is the first shape parameter and b > 0 is the second shape parameter.

## Usage

var logpdf = require( '@stdlib/math/base/dists/kumaraswamy/logpdf' );


#### logpdf( x, a, b )

Evaluates the natural logarithm of the probability density function (PDF) for a Kumaraswamy's double bounded distribution with parameters a (first shape parameter) and b (second shape parameter).

var y = logpdf( 0.5, 1.0, 1.0 );
// returns 0.0

y = logpdf( 0.5, 2.0, 4.0 );
// returns ~0.523

y = logpdf( 0.2, 2.0, 2.0 );
// returns ~-0.264

y = logpdf( 0.8, 4.0, 4.0 );
// returns ~0.522

y = logpdf( -0.5, 4.0, 2.0 );
// returns -Infinity

y = logpdf( -Infinity, 4.0, 2.0 );
// returns -Infinity

y = logpdf( 1.5, 4.0, 2.0 );
// returns -Infinity

y = logpdf( +Infinity, 4.0, 2.0 );
// returns -Infinity


If provided NaN as any argument, the function returns NaN.

var y = logpdf( NaN, 1.0, 1.0 );
// returns NaN

y = logpdf( 0.0, NaN, 1.0 );
// returns NaN

y = logpdf( 0.0, 1.0, NaN );
// returns NaN


If provided a <= 0, the function returns NaN.

var y = logpdf( 2.0, -1.0, 0.5 );
// returns NaN

y = logpdf( 2.0, 0.0, 0.5 );
// returns NaN


If provided b <= 0, the function returns NaN.

var y = logpdf( 2.0, 0.5, -1.0 );
// returns NaN

y = logpdf( 2.0, 0.5, 0.0 );
// returns NaN


#### logpdf.factory( a, b )

Returns a function for evaluating the natural logarithm of the probability density function (PDF) for a Kumaraswamy's double bounded distribution with parameters a (first shape parameter) and b (second shape parameter).

var mylogpdf = logpdf.factory( 0.5, 0.5 );

var y = mylogpdf( 0.8 );
// returns ~0.86

y = mylogpdf( 0.3 );
// returns ~0.679


## Examples

var randu = require( '@stdlib/random/base/randu' );
var EPS = require( '@stdlib/constants/math/float64-eps' );
var logpdf = require( '@stdlib/math/base/dists/kumaraswamy/logpdf' );

var a;
var b;
var x;
var y;
var i;

for ( i = 0; i < 10; i++ ) {
x = randu();
a = ( randu()*5.0 ) + EPS;
b = ( randu()*5.0 ) + EPS;
y = logpdf( 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 ) );
}