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.

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License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.