Time Series Analysis and Its Applications: With R Examples (Springer Texts in Statistics)
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)