Dear R-users,
I'm trying to model some data using a tweedie GLM approach. My response
variable is the number of pupae that are the offspring of a subordinate wasp
on a wasp's nest. However, they're not count data- for each nest, I only
know the mean number of pupae per subordinate, which is continous. The data
also contain a high proportion of zeros.
This worked fine, and gave results I expected, but I don't know what the
best method is to evaluate the fit of the model. I am used to using AIC to
compare models. A site search turned up AICtweedie, within the tweedie
package, but I get the following message: Error: could not find function
"AICtweedie" when I try to use this command, even though "tweedie" and
"statmod" are both loaded. I've also read that AIC can be calculated using
dtweedie, but I'm a beginner and so, despite lots of searching, I'm not sure
how. I'm sorry to ask a basic statistics rather than programming question,
but I'm really stuck. Could anyone advise me on the best way to assess
goodness-of-fit for this type of model, in order to compare models?