function pdf( x, mu, sigma ) {
	var s2;
	var A;
	var B;
	if (
		isnan( x ) ||
		isnan( mu ) ||
		isnan( sigma ) ||
		sigma < 0.0
	) {
		return NaN;
	}
	if ( sigma === 0.0 ) {
		return ( x === mu ) ? PINF : 0.0;
	}
	s2 = pow( sigma, 2.0 );
	A = 1.0 / sqrt( s2*TWO_PI );
	B = -1.0 / ( 2.0*s2 );
	return A * exp( B * pow(x-mu, 2.0) );
}
Evaluates the probability density function (PDF) for a normal distribution with mean `mu` and standard deviation `sigma` at a value `x`.

@param {number} x - input value
@param {number} mu - mean
@param {NonNegativeNumber} sigma - standard deviation
@returns {number} evaluated probability density function

@example
var y = pdf( 2.0, 0.0, 1.0 );
// returns ~0.054

@example
var y = pdf( -1.0, 4.0, 2.0 );
// returns ~0.009

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

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

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

@example
// Negative standard deviation:
var y = pdf( 2.0, 0.0, -1.0 );
// returns NaN

@example
var y = pdf( 2.0, 8.0, 0.0 );
// returns 0.0

@example
var y = pdf( 8.0, 8.0, 0.0 );
// returns Infinity