function cdf( x, N, K, n ) {
	var denom;
	var probs;
	var num;
	var ret;
	var i;

	if (
		isnan( x ) ||
		isnan( N ) ||
		isnan( K ) ||
		isnan( n ) ||
		!isNonNegativeInteger( N ) ||
		!isNonNegativeInteger( K ) ||
		!isNonNegativeInteger( n ) ||
		N === PINF ||
		K === PINF ||
		K > N ||
		n > N
	) {
		return NaN;
	}
	x = trunc( x );
	if ( x < max( 0, n+K-N ) ) {
		return 0.0;
	}
	if ( x >= min( n, K ) ) {
		return 1.0;
	}

	probs = new Float64Array( x+1 );
	probs[ x ] = pmf( x, N, K, n );

	/*
	* Use recurrence relation:
	*
	*   (x+1)( N - K - (n-x-1))P(X=x+1)=(K-x)(n-x)P(X=x)
	*/
	for ( i = x-1; i >= 0; i-- ) {
		num = ( i+1 ) * ( N-K-(n-i-1) );
		denom = ( K-i ) * ( n-i );
		probs[ i ] = ( num/denom ) * probs[ i+1 ];
	}
	ret = sum( probs );
	return min( ret, 1.0 );
}
Evaluates the cumulative distribution function (CDF) for a hypergeometric distribution with population size `N`, subpopulation size `K`, and number of draws `n` at a value `x`.

@param {number} x - input value
@param {NonNegativeInteger} N - population size
@param {NonNegativeInteger} K - subpopulation size
@param {NonNegativeInteger} n - number of draws
@returns {Probability} evaluated CDF

@example
var y = cdf( 1.0, 8, 4, 2 );
// returns ~0.786

@example
var y = cdf( 1.5, 8, 4, 2 );
// returns ~0.786

@example
var y = cdf( 2.0, 8, 4, 2 );
// returns 1.0

@example
var y = cdf( 0, 8, 4, 2 );
// returns ~0.214

@example
var y = cdf( NaN, 10, 5, 2 );
// returns NaN

@example
var y = cdf( 0.0, NaN, 5, 2 );
// returns NaN

@example
var y = cdf( 0.0, 10, NaN, 2 );
// returns NaN

@example
var y = cdf( 0.0, 10, 5, NaN );
// returns NaN

@example
var y = cdf( 2.0, 10.5, 5, 2 );
// returns NaN

@example
var y = cdf( 2.0, 10, 1.5, 2 );
// returns NaN

@example
var y = cdf( 2.0, 10, 5, -2.0 );
// returns NaN

@example
var y = cdf( 2.0, 10, 5, 12 );
// returns NaN

@example
var y = cdf( 2.0, 8, 3, 9 );
// returns NaN