ABSTRACT

In many applications, including marketing, we observe at different times and for different subjects counts of some event of interest. Accurate modeling of such time series of counts (responses) for N subjects over T time periods as functions of relevant covariates (subject-specific and time-varying), and incorporating dependence over time, is becoming increasingly important in several applications. In situations where we observe a vector of counts for each subject at each time, we are also interested in incorporating the association between the components of the count vectors. In this chapter, we describe the modeling of univariate and multivariate time series of counts in the context of a marketing application that involves modeling/predicting product sales.