Stationarity of a general class of observation driven models for discrete valued processes

A large variety of time series observation-driven models for binary and count data are currently used in different contexts. Despite the importance of station- arity and ergodicity to ensure suitable results, for many of these models stationarity is not yet proved. We specify a general class of observation-driven models for dis- crete valued processes, which encompasses the most frequently used models. Then, we show strict stationarity by means of Feller properties and establish easy-to-check stationarity conditions.