I have a dataset with count variable of 50 observation and 260 independent variables. As the variance exceeds mean, I want to use Negative Binomial distribution. My objective is to build a model that can be used for future prediction. So, a model validation is required. Given that my p exceeds n, I need to use penalized regression, like lasso or Elastic net. With the R package "mpath", I can find the best subset but not the coefficient estimate and P- value. The "Glmnet" package doesn't have negative binomial or P-value. The "BeSS" package gives P-value but not for NB model. The "GLMMLasso" package looks promising but again not for NB only Poisson.
Can anyone help me with suggestions which method should I use for my subset selection, model building, and validation? Is there any package in R or SAS? Thanks in advance