function factory( a, b, mu, sigma ) {
	var s2x2;
	var A;
	var B;
	var C;

	if (
		isnan( a ) ||
		isnan( b ) ||
		isnan( mu ) ||
		isnan( sigma ) ||
		sigma <= 0.0 ||
		a >= b
	) {
		return constantFunction( NaN );
	}
	s2x2 = 2.0 * pow( sigma, 2.0 );
	A = 1.0 / ( sqrt( s2x2 * PI ) );
	B = -1.0 / ( s2x2 );
	C = normalCDF( (b-mu)/sigma ) - normalCDF( (a-mu)/sigma );
	return pdf;

	/**
	* Evaluates the probability density function (PDF) for a truncated normal distribution.
	*
	* @private
	* @param {number} x - input value
	* @returns {number} evaluated PDF
	*/
	function pdf( x ) {
		if ( isnan( x ) ) {
			return NaN;
		}
		if ( x < a || x > b ) {
			return 0.0;
		}
		return A * exp( B * pow( x - mu, 2.0 ) ) / C;
	}
}
Returns a function for evaluating the probability density function (PDF) for a truncated normal distribution with endpoints `a` and `b`, mean `mu` and standard deviation `sigma`.

@param {number} a - minimum support
@param {number} b - maximum support
@param {number} mu - location parameter
@param {PositiveNumber} sigma - scale parameter
@returns {Function} PDF

@example
var myPDF = factory( 0.0, 1.0, 0.0, 1.0 );
var y = myPDF( 0.8 );
// returns ~0.849

@example
var myPDF = factory( 0.0, 1.0, 0.5, 1.0 );
var y = myPDF( 0.8 );
// returns ~0.996

@example
var myPDF = factory( 0.0, 1.0, 0.0, 1.0 );
var y = myPDF( 2.0 );
// returns 0.0

@example
var myPDF = factory( 0.0, 1.0, 0.0, 1.0 );
var y = myPDF( -1.0 );
// returns 0.0