Consistent model selection procedure for general integer-valued time series

This paper deals with model selection for a general class of integer-valued time series. We propose penalized criterion based on the Poisson quasi-likelihood model. Under certain regularity conditions, consistency procedure as well and asymptotic normality estimator selected are established. Simulation experiments conducted some classical models such negative binomial linear nonlinear dynamics. Also, an application to real dataset is provided.