Weibull<-function(tet1, tet2,x){
1-exp(-exp(tet1+tet2*log10(x)))
}
range(effectdata_without_controls$conc)
# 0.000135696 0.000247044
range(effectdata_without_controls$effect)
# [1] -7.010672 100.240287
nls(effect ~ Weibull(tet1, tet2, conc))
Your Weibull function has a range of
I'm not the author of nlsModel, so would prefer not to tinker with it.
But "singular gradient" is a VERY common problem with nls() that is used
by nlsModel as I understand it. The issue is actually a singular
Jacobian matrix resulting from a rather weak approximation of the
derivatives (a simple f
Hi
I do not want to dig too deep into your code so only 2 comments.
1.Try to plot your defined functions with starting parameters and with defined
concentration
something like
plot(conc, Weibull(1,1, conc))
2.Try to use conc with different units, something like
conc1 <- conc*1000
Cheers
Pet
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