timed.parallel.sensitivity <-function(
###function calculate PRCC sensitivity coefficients of the model parameters along whole timeline of the model execution,
res,##<<data frame of parameter sets. Each row is a set, each column is a parameter
obsSens,##<<data frame of observables obtained in the model simulations
outName="Prot[0-9]+",##<<name of observable to calculate sensitivity
nboot=0,##<<number of bootstrap runs
plot=FALSE##<<flag should be true, if graphical representation is required
){
return(timed.concurrent.sensitivity(res=res,obsSens=obsSens,outName=outName,nboot=nboot,plot=plot))
}
timed.concurrent.sensitivity <-function(
###function calculate PRCC sensitivity coefficients of the model parameters along whole timeline of the model execution,
res,##<<data frame of parameter sets. Each row is a set, each column is a parameter
obsSens,##<<data frame of observables obtained in the model simulations
outName="Prot[0-9]+",##<<name of observable to calculate sensitivity
nboot=0,##<<number of bootstrap runs
plot=FALSE##<<flag should be true, if graphical representation is required
){
timedSC<-data.frame(time=0,param='',value=0,pval=0)[FALSE,]
for(i in unique(obsSens$time)){
cs0<-concurrent.sensitivity(res,obsSens[obsSens$time==i,],outName,nboot)
timedSC<-rbind(timedSC,cbind(data.frame(time=i,param = rownames(cs0$prcc)),cs0$prcc))
cat(paste(i,'\n'))
}
attr(timedSC,'N')<-cs0$N
attr(timedSC,'p')<-cs0$p
return(timedSC);
###data frame of parameter PRCC coefficients at each time point
}
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