[R-sig-ME] zero-truncated negative binomial distribution

[Alice Domalik]

Hi all, 

I am fitting mixed effects models using the package glmmTMB to investigate habitat use. 
My data does not contain any zeros, so I have considered the zero-truncated poisson and the zero-truncated negative binomial. 
Of these two distributions, the zt negative binomial was better, so I tried fitting my model: 

m1<-glmmTMB(count~waterdepth + temperature + chl.conc + (1|individual), family=list(family="truncated_nbinom1", link="log"), data=mydata) 

However, it is clear that the model is having a hard time fitting my very high response values (the distribution of my response variable has a very long tail). 
The QQplot also shows the high 'count' values being above the QQline. 

What are my options for improving model fit? Are there any distributions that might be better? Is it permissible to transform my response variable (eg. sqrt or log)? 

Any suggestions are greatly appreciated. 

-Ally 


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