We discuss some models for the statistical analysis of binary and count time series based on generalized linear models methodology. We outline the methods and tools needed for studying such models and we develop maximum likelihood estimation theory and diagnostics. The theory is extended to the general framework of time series following generalized linear models. Several real data examples complement the presentation.
