lib/index.js
function getPDF( mu, s2 ) {
		var A = 1 / (  Math.sqrt(s2*2*Math.PI) ),
			B = -1 / (2*s2);
		/**
		* FUNCTION: pdf( x )
		*	Evaluates the probability distribution function at input value `x`.
		*
		* @private
		* @param {Number} x - input value
		* @returns {Number} evaluated PDF
		*/
		return function pdf( x ) {
			var C = x - mu;
			return A * Math.exp( B*C*C );
		};
	}
function getPDF( mu, s2 ) {
		var A = 1 / (  Math.sqrt(s2*2*Math.PI) ),
			B = -1 / (2*s2);
		/**
		* FUNCTION: pdf( x )
		*	Evaluates the probability distribution function at input value `x`.
		*
		* @private
		* @param {Number} x - input value
		* @returns {Number} evaluated PDF
		*/
		return function pdf( x ) {
			var C = x - mu;
			return A * Math.exp( B*C*C );
		};
	}
FUNCTIONS // 
FUNCTION: getPDF( mu, variance )
Returns a probability density function for a normal distribution with mean `mu` and variance `s2`.

@private
@param {Number} mu - distribution mean
@param {Number} variance - distribution variance
@returns {Function} probability density function (PDF)