[R] multinom(): likelihood of model?

[Brooks Miner]

Hi all,

I'm working on a multinomial (or "polytomous") logistic regression 
using R and have made great progress using multinom() from the nnet 
library.  My response variable has three categories, and there are two 
different possible predictors.  I'd like to use the likelihoods of 
certain models (ie, saturated, fitteds, and null) to calculate 
Nagelkerke R-squared values for various fitted models.

My question today is simple: once I have fitted a model using 
multinom(), how do I find the likelihood (or log likelihood) of my 
fitted model?  I understand that this value must be part of the 
$deviance or $AIC components of the fitted model, but my understanding 
is too limited at this point for me to know how to calculate the 
likelihood of my fitted model from either of these outputs.

Thanks in advance to any assistance offered.  I'd be happy to provide 
an example of my data and multinom() entries if that would help.

Gratefully,

- Brooks
----------------------------
Brooks Miner
Research Scientist
Laird Lab
UW Biology
206.616.9385
http://protist.biology.washington.edu/Lairdlab/