QFA logistic parameter bounds.

makeBounds.R

makeBoundsQFA<-function(inocguess,d,minK=0,fixG=FALSE,globalOpt=FALSE){

	if(is.null(inocguess)){
		# Without a sensible independent estimate for inoculum density, the best we can do is to estimate it based on observed data.
		# This strategy will only work well if the inoculum density is high enough to be measurable (e.g. pinned cultures or 
		# conc. spotted) and is clearly observed.  Clearly observed means: no condensation on plates immediately after they are 
		# placed in incubator for example.
		if(length(d$Growth)>0) {candidate=min(d$Growth)}else{candidate=0}
		inocguess=max(0.001,candidate)
	}
	
	# Define optimization bounds based on inocguess #
	lowr<-0; upr<-25
	lowv<-0.1; upv<-10.0
	lowK<-max(0.9*inocguess,minK); upK<-1.0
		
	# We often fix inoculation density, but users might prefer to infer it from growth curves
	if(fixG) {lowg<-0.9*inocguess; upg<-1.1*inocguess}else{lowg<-0.01*inocguess; upg<-100.0*inocguess}
	if(globalOpt) lowg<-1e-6*inocguess; upg<-1e6*inocguess
	
	lowg<-max(0,lowg); upg<-min(upK,upg) 
	
	return(list(K=c(lowK,upK),r=c(lowr,upr),g=c(lowg,upg),v=c(lowv,upv),inocguess=inocguess))
}