I'm doing a non linear regression with 8 parameters to be fitted:
J.Tl.nls<-nls(Gw~(a1/(1+exp(-a2*Tl+a3))+a4)*(b1/(1+exp(b2*Tl-b3))+b4),data=Enveloppe,
start=list(a1=0.88957,a2=0.36298,a3=10.59241,a4=0.26308,
b1=0.391268,b2=1.041856,b3=0.391268,b4=0.03439))
First, I fitted my curve on my data by guessing the parameters' values ("by
hand"), and wrote them.
Then, I ajusted my model only with two parameters (whereas the others were
fixed with previously found values, I did it the same way for all parameters.
Finally, I got 8 fitted values that I enventually embedded in my nls()
function, like above, yet R talled me:
"Error in nlsModel(formula, mf, start) : singular gradient matrix at initial
parameter estimates"
should I use optim() or optimize()?
How could I perform it?
Thanks for help
Guillaume Storchi
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