"Time Series Analysis and Its Applications" presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using non-trivial data illustrate solutions to problems such as evaluating pain perception experiments using magnetic resonance imaging or monitoring a nuclear test ban treaty. The book is designed to be useful as a text for graduate level students in the physical, biological and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. Material from the earlier 1988 Prentice-Hall text "Applied Statistical Time Series Analysis" has been updated by adding modern developments involving categorical time series analysis and the spectral envelope, multivariate spectral methods, long memory series, nonlinear models, longitudinal data analysis, resampling techniques, ARCH models, stochastic volatility, wavelets and Monte Carlo Markov chain integration methods. These add to a classical coverage of time series regression, univariate and multivariate ARIMA models, spectral analysis and state-space models. The book is complemented by offering accessibility, via the World Wide Web, to the data and an exploratory time series analysis program ASTSA for Windows that can be downloaded as Freeware. Robert H. Shumway is Professor of Statistics at the University of California, Davis. He is a Fellow of the American Statistical Association and a member of the International Statistical Institute. He won the 1986 American Statistical Association Award for Outstanding Statistical Application and the 1992 Communicable Diseases Center Statistics Award; both awards were for joint papers on time series applications. He is the author of a previous 1988 Prentice-Hall text.
From the reviews of the second edition:
"The book gives an introduction to time series analysis. It is designed as a textbook at both the undergraduate and graduate level and as a reference work for practitioners ... . This now available second edition of the book differs from the first ... by several substantial changes. ... the presentation has improved. The consideration of new material makes it more attractive as well. Moreover, the use of the R package ... makes the book more interesting ... ." (Wolfgang Schmid, Zentrablatt MATH, Vol. 1096 (22), 2006)
"This is the second edition of a text first published in 2000 ... . The text is intended as a course text for a time series analysis class at the graduate level. ... I believe that every time series teacher and researcher should own this text." (Robert Lund, Journal of the American Statistical Association, Vol. 102 (479), 2007)
"This is the second edition of a text first published in 2000 ... . The book is intended as a course text for a graduate-level time series analysis class. It presents a very readable introduction to time series, and uses numerous examples based on nontrivial data to illustrate the methods. ... Altogether, the book offers a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Compared to other established texts, it presents a more modern slice of the discipline." (Rainer Schlittgen, Advances in Statistical Analysis, Vol. 92, 2008)
"A textbook aimed at graduate-level students, while ... the book could also serve as an undergraduate introductory course in time series analysis. ... The clear division between time and frequency domain methods produces a well balanced and comprehensive treatment of modern time series analysis ... . The book certainly fulfils its claim to be suitable as a textbook for courses at both the undergraduate and graduate levels, as tutors can pick and choose from an abundance of material at different levels of complexity." (Pieter Bastiaan Ober, Journal of Applied Statistics, Vol. 35 (2), 2008)
