Time Series Analysis: Nonstationary and Noninvertible Distribution Theory

We deal with linear time series models on which stationarity or invertibility is not imposed. Using simple examples arising from estimation and testing problems we indicate nonstandard aspects of the departure from stationarity or invertibility. In particular, asymptotic distributions of various statistics are derived by the eigenvalue approach under the normality assumption on the underlying processes. As a prelude to discussions in later chapters we also present equivalent expressions for limiting random variables based on the other approaches.