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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