# NOT RUN {
## First 4 runs and return parameters of fit
## do background subtraction using mean the first 5 cycles.
pcrbatch(reps, fluo = 2:5, baseline = "mean", basecyc = 1:5)
# }
# NOT RUN {
## First 8 runs, with 4 replicates each, l5 model.
pcrbatch(reps, fluo = 2:9, model = l5, group = c(1,1,1,1,2,2,2,2))
## Using model selection (Akaike weights)
## on the first 4 runs, runs 1 and 2 are replicates.
pcrbatch(reps, fluo = 2:5, group = c(1,1,2,3),
opt = TRUE, optPAR = list(crit = "weights"))
## Fitting a sigmoidal and 'mak3' mechanistic model.
pcrbatch(reps, methods = c("sigfit", "mak3"))
## Converting a 'modlist' to 'pcrbatch'.
ml5 <- modlist(reps, 1, 2:5, b5)
res5 <- pcrbatch(ml5)
## Using Whittaker smoothing.
pcrbatch(reps, smooth = "whit")
# }
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