# Logarithm of Probability Mass Function

Evaluate the natural logarithm of the probability mass function (PMF) for a hypergeometric distribution.

Imagine a scenario with a population of size N, of which a subpopulation of size K can be considered successes. We draw n observations from the total population. Defining the random variable X as the number of successes in the n draws, X is said to follow a hypergeometric distribution. The probability mass function (PMF) for a hypergeometric random variable is given by

## Usage

var logpmf = require( '@stdlib/math/base/dists/hypergeometric/logpmf' );


#### logpmf( x, N, K, n )

Evaluates the natural logarithm of the probability mass function (PMF) for a hypergeometric distribution with parameters N (population size), K (subpopulation size), and n (number of draws).

var y = logpmf( 1.0, 8, 4, 2 );
// returns ~-0.56

y = logpmf( 2.0, 8, 4, 2 );
// returns ~-1.54

y = logpmf( 0.0, 8, 4, 2 );
// returns ~-1.54

y = logpmf( 1.5, 8, 4, 2 );
// returns -Infinity


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

var y = logpmf( NaN, 10, 5, 2 );
// returns NaN

y = logpmf( 0.0, NaN, 5, 2 );
// returns NaN

y = logpmf( 0.0, 10, NaN, 2 );
// returns NaN

y = logpmf( 0.0, 10, 5, NaN );
// returns NaN


If provided a population size N, subpopulation size K, or draws n which is not a nonnegative integer, the function returns NaN.

var y = logpmf( 2.0, 10.5, 5, 2 );
// returns NaN

y = logpmf( 2.0, 10, 1.5, 2 );
// returns NaN

y = logpmf( 2.0, 10, 5, -2.0 );
// returns NaN


If the number of draws n exceeds population size N, the function returns NaN.

var y = logpmf( 2.0, 10, 5, 12 );
// returns NaN

y = logpmf( 2.0, 8, 3, 9 );
// returns NaN


#### logpmf.factory( N, K, n )

Returns a function for evaluating the natural logarithm of the probability mass function (PMF) of a hypergeometric distribution with parameters N (population size), K (subpopulation size), and n (number of draws).

var mylogpmf = pmf.factory( 30, 20, 5 );
var y = mylogpmf( 4.0 );
// returns ~-1.079

y = mylogpmf( 1.0 );
// returns ~-3.54


## Examples

var randu = require( '@stdlib/random/base/randu' );
var round = require( '@stdlib/math/base/special/round' );
var logpmf = require( '@stdlib/math/base/dists/hypergeometric/logpmf' );

var i;
var N;
var K;
var n;
var x;
var y;

for ( i = 0; i < 10; i++ ) {
x = round( randu() * 5.0 );
N = round( randu() * 20.0 );
K = round( randu() * N );
n = round( randu() * N );
y = logpmf( x, N, K, n );
console.log( 'x: %d, N: %d, K: %d, n: %d, ln(P(X=x;N,K,n)): %d', x, N, K, n, y.toFixed( 4 ) );
}