Mixed INAR(1) Poisson regression models: Analyzing heterogeneity and serial dependencies in longitudinal count data

This paper presents finite mixture versions of integer-valued autoregressive (INAR) Poisson regression models for investigating regularity and predictability of purchase behavior over time. The approach facilitates the analysis of heterogeneity and serial correlation effects as well as conditional and marginal analyses of the effects of covariates. An application to scanner panel data of detergents yields substantive insights into sources of autodependencies in individual category purchases.