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Proponha solução(ções) para o seguinte post:

I would like to get parameter estimates for different models. For one of them I give the code in example. I am estimating the parameters (i,j and k) with the nls function, which sees the error distribution as normal, I would however like to do the same as nls with the assumption that the errors are poisson distributed. Is there a way to do this with R? Are there packages designed for this? I tried with the gnm package, but don't understand how to transform my equation to a generalised equation. Is there an option for nls to choose family = poisson? Lower in the mail the code with the model and visualisations I use to check my results. I also copied the test dataset from my txt file. I am using R 2.15 and Rstudio to visualise it.

plot(FR~N0)
x <-
nls(FR~(exp(i+j*N0)/(1+exp(i+j*N0)))*(k*N0/(k+N0)),start=list(i=0.02,j=0.002,k=6))
summary(x)
hatx <- predict(x)
lines(spline(N0,hatx))

N0      FR
10      2
10      3
10      2
10      4
10      2
10      2
10      1
10      2
10      2
10      2
20      2
20      3
20      3
20      3
20      4
20      2
20      4
20      2
20      3
20      2
30      1
30      2
30      3
30      4
30      5
30      6
30      2
30      3
30      2
30      2
40      2
40      3
40      3
40      6
40      5
40      4
40      3
40      3
40      2
40      3
50      4
50      5
50      2
50      3
50      7
50      5
50      4
50      3
50      4
50      5
60      5
60      6
60      8
60      4
60      4
60      3
60      2
60      2
60      5
60      4