Observation-driven model is a term generally applied to models for the longitudinal data or time series which introduce within the unit correlation by specifying the conditional distribution of an observation at the time t as a function of previous observations. An instance is the ante- dependence model. In contrast in the parameter-driven model, correlation is introduced during a latent process, for instance, by introducing a random subject effect.