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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
Installation
npm install @stdlib/stats-base-dists-hypergeometric-logpmf
Usage
var logpmf = require( '@stdlib/stats-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
or the subpopulation size K
exceed 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 = logpmf.factory( 30, 20, 5 );
var y = mylogpmf( 4.0 );
// returns ~-1.079
y = mylogpmf( 1.0 );
// returns ~-3.524
Examples
var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var logpmf = require( '@stdlib/stats-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 ) );
}
Notice
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
Community
License
See LICENSE.
Copyright
Copyright © 2016-2024. The Stdlib Authors.