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

	if (
		isnan( x ) ||
		isnan( a ) ||
		isnan( b ) ||
		sigma <= 0.0 ||
		a >= b
	) {
		return NaN;
	}
	if ( x < a || x > b ) {
		return 0.0;
	}
	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 A * exp( B * pow( x - mu, 2.0 ) ) / C;
}
Evaluates the probability density function (PDF) for a truncated normal distribution with endpoints `a` and `b`, location parameter `mu` and scale parameter `sigma` at a value `x`.

@param {number} x - input value
@param {number} a - minimum support
@param {number} b - maximum support
@param {number} mu - location parameter
@param {PositiveNumber} sigma - scale parameter
@returns {number} evaluated PDF

@example
var y = pdf( 0.9, 0.0, 1.0, 0.0, 1.0 );
// returns ~0.7795

@example
var y = pdf( 0.9, 0.0, 1.0, 0.5, 1.0 );
// returns ~0.9617

@example
var y = pdf( 0.9, -1.0, 1.0, 0.5, 1.0 );
// returns ~0.5896

@example
var y = pdf( 1.4, 0.0, 1.0, 0.0, 1.0 );
// returns 0.0

@example
var y = pdf( -0.9, 0.0, 1.0, 0.0, 1.0 );
// returns 0.0