General Linear Processes: Wold Decomposition Theorem

This lecture by the instructor covers general linear processes, the Wold decomposition theorem, and the properties of stationary processes. It explains the one-sided linear representation of processes, the predictability of singular processes, and the concept of invertibility in the context of time series analysis. The lecture also delves into the function G(z), its Laurent series, and the implications of the roots of G(z) and G-1(z) on the stationarity and invertibility of models. Spectral analysis of stationary stochastic processes and the orthogonal increment process are discussed, emphasizing the importance of orthogonality in analyzing complex-valued processes.