ABSTRACT
Autoregressive time series models are central to stationary time series data analysis and, as components of larger models or in suitably modified and generalized forms, underlie nonstationary time-varying models. The concepts and structure of linear autoregressive models also provide important background material for appreciation of nonlinear models. This chapter discusses model forms and inference for autoregressions and related topics. This is followed by discussion of the class of stationary autoregressive, moving average models.
