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
ers
Petr
> -Original Message-
> From: R-help On Behalf Of Belinda Hum Bei Lin
> Sent: Monday, October 8, 2018 11:15 AM
> To: r-help@r-project.org
> Subject: [R] Error in nlsModel
>
> Hello,
>
> It is my first time using R studio and I am facing the error of
&g
Hello,
It is my first time using R studio and I am facing the error of
"Error in nlsModel(formula, mf, start, wts) :
singular gradient matrix at initial parameter estimates"
when I try to run my script. From what I read online, I understand that the
error might be due to the parameters. However,
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