[R-sig-ME] glmmTMB negbinom not working with spatial autocorrelation

[Bansal, Udita]

Hello all,

I had been running a mixed model with poisson distribution of the following type, with a spatial autocorrelation term, which works fine:

Y(count data) ~ x1 + square(x1) + x2 + square(x2) + exp( ) + (1|population/species)

I realized that my dataset has a lot of small values (mostly 1 and 2) and some large values, so that the data is highly skewed and over dispersed. So I tried to run the following negbinom1 model:

Y(count data) ~ x1 + square(x1) + x2 + square(x2) + exp( ) + (1|population/species) + ziformula = ~.

This time the model doesn’t run and says it cannot find one of the independent variables in the dataset. If I remove that variable from the model then it says so for another variable and so on. If I remove the factor for spatial autocorrelation, the model seems to work fine. Can anyone tell me what’s happening and if what I am doing is appropriate for a highly skewed and over dispersed dataset?

Thank you
Udita Bansal
Project Assistant
Centre for Ecological Sciences
Indian Institute of Science
India


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