
Hi,
 
I am trying to use a non linear regresion form like: f(x) ~ fmax*(1-exp(-a*(x-c)).
 
> nls.NEE.fill <- nls(NEE ~ -NEE.max*(1-exp(-alpha*(PAR-I))), start=list(NEE.max=-25,alpha=5,I=20))
 
I have given random values to a and c (alpha and I). But it gives my an error: 
 
Error in nlsModel(formula, mf, start) : singular gradient matrix at initial parameter estimates
 
 
Before that I used other nls, because I had used it for other data set and worked without errors. 
 
> nls.NEE.fill <- nls(NEE ~ offset + (NEE.max*PAR)/(alpha + PAR), start=list (NEE.max=-25, alpha=0.5, offset=5)) 
 
But for this dataset it gives the following:
 
Error in numericDeriv(form[[3]], names(ind), env) :         Missing value or an infinity produced when evaluating the model 
What should I do?
 
Thank you
 
All my best
 
Laura
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