This text emphasizes nonlinear models for a course in time series analysis. After introducing stochastic processes, Markov chains, Poisson processes, and ARMA models, the authors cover functional autoregressive, ARCH, threshold AR, and discrete time series models as well as several complementary...

Deals with analyzing and forecasting multiple time series, considering a range of models and methods. This reference work and graduate-level textbook enables readers to perform their analyses in a competent manner