function pdf( x, mu, sigma ) {
	if ( sigma === 0 ) {
		return x === mu ? Number.POSITIVE_INFINITY : 0;
	}
	var s2 = pow( sigma, 2 ),
		A = 1 / ( sqrt( 2 * s2 * PI ) ),
		B = -1 / ( 2 * s2 );
	return A * exp( B * pow( x - mu, 2 ) );
}
function pdf( x, mu, sigma ) {
	if ( sigma === 0 ) {
		return x === mu ? Number.POSITIVE_INFINITY : 0;
	}
	var s2 = pow( sigma, 2 ),
		A = 1 / ( sqrt( 2 * s2 * PI ) ),
		B = -1 / ( 2 * s2 );
	return A * exp( B * pow( x - mu, 2 ) );
}
function pdf ( x , mu , sigma ) { if ( sigma === 0 ) { return x === mu ? Number . POSITIVE_INFINITY : 0 ; } var s2 = pow ( sigma , 2 ) , A = 1 / ( sqrt ( 2 * s2 * PI ) ) , B = - 1 / ( 2 * s2 ) ; return A * exp ( B * pow ( x - mu , 2 ) ) ; }
PDF // 
FUNCTION: pdf( x, mu, sigma )
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 {Number} sigma - standard deviation
@returns {Number} evaluated PDF
PDF // FUNCTION : pdf ( x mu sigma ) Evaluates the probability density function ( PDF ) for a Normal distribution with mean mu and standard deviation sigma at a value x .