function factory( r, p ) {
	var sigmaInv;
	var sigma;
	var mu;
	var q;
	if (
		isnan( r ) ||
		isnan( p ) ||
		r <= 0.0 ||
		p < 0.0 ||
		p > 1.0
	) {
		return constantFunction( NaN );
	}
	q = 1.0 - p;
	mu = ( r * q ) / p;
	sigma = sqrt( r * q ) / p;
	sigmaInv = ( (2.0/p) - 1.0 ) / sigma;
	return quantile;

	/**
	* Evaluates the quantile function for a negative binomial distribution.
	*
	* @private
	* @param {Probability} k - input value
	* @returns {NonNegativeInteger} evaluated quantile function
	*
	* @example
	* var y = quantile( 0.3 );
	* // returns <number>
	*/
	function quantile( k ) {
		var guess;
		var corr;
		var x2;
		var x;

		if ( isnan( k ) || k < 0.0 || k > 1.0 ) {
			return NaN;
		}
		if ( k === 0.0 ) {
			return 0.0;
		}
		if ( k === 1.0 ) {
			return PINF;
		}

		// Cornish-Fisher expansion:
		if ( k < 0.5 ) {
			x = -erfcinv( 2.0 * k ) * SQRT2;
		} else {
			x = erfcinv( 2.0 * (1.0-k) ) * SQRT2;
		}
		x2 = x * x;

		// Skewness correction:
		corr = x + (sigmaInv * ( x2 - 1.0 ) / 6.0);
		guess = round( mu + (sigma * corr) );
		return ( cdf( guess, r, p ) >= k ) ?
			search.left( guess, k, r, p ) :
			search.right( guess, k, r, p );
	}
}
Returns a function for evaluating the quantile function for a negative binomial distribution with number of successes until experiment is stopped `r` and success probability `p`.

@param {PositiveNumber} r - number of successes until experiment is stopped
@param {Probability} p - success probability
@returns {Function} quantile function

@example
var quantile = factory( 10.0, 0.5 );
var y = quantile( 0.1 );
// returns 5

y = quantile( 0.9 );
// returns 16