## normSD function: Compute standard deviation of normally distributed noise
## Arg 1: Number of non-zero representational elements in underlying form
## Arg 2: Number of non-zero representational elements in target surface representation that are distinct from error
## Arg 3: Number of non-zero representational elements in error surface representation that are distinct from target 
## Arg 4: Harmony advantage of target over error
## Arg 5: Error rate

## Returns standard deviation of noise function

normErrSD.fnc = function (underlying, uniqueTarget, uniqueError, common, harmonyAdvantage, errRate) {

if(uniqueTarget+common > 1){
	if(common>1){
		markNTarget = length(combn(uniqueTarget+common,2,simplify=F))  -length(combn(common,2,simplify=F)) 
		}else
		markNTarget = length(combn(uniqueTarget+common,2,simplify=F))
		}else
		markNTarget = 0

if(uniqueError+common > 1){
	if(common>1){
		markNError = length(combn(uniqueError+common,2,simplify=F))  -length(combn(common,2,simplify=F)) 
		}else
		markNError = length(combn(uniqueError+common,2,simplify=F))
		}else
		markNError = 0

faithNTarget = underlying * uniqueTarget
faithNError = underlying * uniqueError

w = qnorm (errRate)

return (sqrt( (-harmonyAdvantage / (w*sqrt ( (faithNTarget+4*markNTarget+faithNError+4*markNError))))^2))

}