whole_func_string: 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 );
  		};
  	}
func_code_string: 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 );
  		};
  	}
func_documentation_string: 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)