Mode
Hypergeometric distribution mode.
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 mode for a hypergeometric random variable is
Usage
var mode = require( '@stdlib/stats/base/dists/hypergeometric/mode' );
mode( N, K, n )
Returns the mode of a hypergeometric distribution with parameters N
(population size), K
(subpopulation size), and n
(number of draws).
var v = mode( 16, 11, 4 );
// returns 3
v = mode( 2, 1, 1 );
// returns 1
If provided NaN
as any argument, the function returns NaN
.
var v = mode( NaN, 10, 4 );
// returns NaN
v = mode( 20, NaN, 4 );
// returns NaN
v = mode( 20, 10, 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 v = mode( 10.5, 5, 2 );
// returns NaN
v = mode( 10, 1.5, 2 );
// returns NaN
v = mode( 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 v = mode( 10, 5, 12 );
// returns NaN
v = mode( 10, 12, 5 );
// returns NaN
Examples
var randu = require( '@stdlib/random/base/randu' );
var round = require( '@stdlib/math/base/special/round' );
var mode = require( '@stdlib/stats/base/dists/hypergeometric/mode' );
var v;
var i;
var N;
var K;
var n;
for ( i = 0; i < 10; i++ ) {
N = round( randu() * 20 );
K = round( randu() * N );
n = round( randu() * K );
v = mode( N, K, n );
console.log( 'N: %d, K: %d, n: %d, mode(X;N,K,n): %d', N, K, n, v.toFixed( 4 ) );
}