## errorProb function: Generate error probabilities
## Returns total number of errors
## Arg 1: Number of samples for Monte Carlo
## Arg 2: Number of non-zero representational elements in underlying form
## Arg 3: Number of non-zero representational elements in target surface representation that are distinct from error
## Arg 4: Number of non-zero representational elements in error surface representation that are distinct from target 
## Arg 5: Harmony advantage of target over error
## Arg 6: Standard deviation of randomly distributed noise

## Returns total number of errors

## NOTE to use a different probability distribution, alter the rnorm statements in the code below.

errorProb.fnc = function (sampleNumber, underlying, uniqueTarget, uniqueError, common, harmonyAdvantage, sdNoise) {

errorCount = 0 # count number of errors

## Calculate number of markedness weights that make a unique contribution to target and error harmony

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

for (j in c(1:sampleNumber)) {
	targetHarmony = sum (rnorm(underlying*uniqueTarget,0,sdNoise))
		# for each faithfulness weight that makes a unique contribution to the target, generate a random disruption
	targetHarmony = targetHarmony + 2*sum(rnorm(markNTarget,0,sdNoise))
		# for each markedness weight that makes a unique contribution to the target, generate a random disruption
	errorHarmony = sum (rnorm(underlying*uniqueError,0,sdNoise))
		# for each faithfulness weight that makes a unique contribution to the error, generate a random disruption
	errorHarmony = errorHarmony + 2*sum(rnorm(markNError,0,sdNoise))
		# for each markedness weight that makes a unique contribution to the target, generate a random disruption
	if (-harmonyAdvantage > (targetHarmony-errorHarmony))
		# if conditions of Corollary 2 are met, error has occurred
		errorCount = errorCount + 1
}
return (errorCount)  # return total number of errors

}