R code is provided simply to enhance the exposition by making the numerical examples reproducible. So there is no misunderstanding, we emphasize the fact that this text is about time series analysis, not about R. Appendix R is new to this edition, and it includes a small R tutorial as well as providing a reference for the data sets and scripts included in tsa3.rda. Specific details are given in Appendix R and on the website for the text.

On the website, we also provide the code used in each example so that the reader may simply copy-and-paste code directly into R. In addition, we provide an R supplement for the text that contains the data and scripts in a compressed file called tsa3.rda the supplement is available on the website for the third edition, , The major difference between this third edition of the text and the second edition is that we provide R code for almost all of the numerical examples. For the upper-level graduate course, we should mention that we are striving for a broader but less rigorous level of coverage than that which is attained by Brockwell and Davis (1991), the classic entry at this level. Finally, a two-semester upper-level graduate course for mathematics, statistics, and engineering graduate students can be crafted by adding selected theoretical appendices. Often, the extra topics are chosen by the students according to their interests. At the advanced undergraduate or master’s level, where the students have some mathematical statistics background, more detailed coverage of the same sections, with the inclusion of §2.4 and extra topics from Chapter 5 or Chapter 6 can be used as a one-semester course. Our experience is that an undergraduate course can be accessible to students with a background in regression analysis and may include §1.1–§1.6, §2.1–§2.3, the results and numerical parts of §3.1– §3.9, and briefly the results and numerical parts of §4.1–§4.6. We have used earlier versions of the text at both the undergraduate and graduate levels over the past decade. This book is designed to be useful as a text for courses in time series on several different levels and as a reference work for practitioners facing the analysis of timecorrelated data in the physical, biological, and social sciences. The advent of inexpensive powerful computing has provided both real data and new software that can take one considerably beyond the fitting of simple time domain models, such as have been elegantly described in the landmark work of Box and Jenkins (1970). The goals of this book are to develop an appreciation for the richness and versatility of modern time series analysis as a tool for analyzing data, and still maintain a commitment to theoretical integrity, as exemplified by the seminal works of Brillinger (1975) and Hannan (1970) and the texts by Brockwell and Davis (1991) and Fuller (1995). To my family and friends, who constantly remind me what is important. Springer is part of Springer Science+Business Media (To my wife, Ruth, for her support and joie de vivre, and to the memory of my thesis adviser, Solomon Kullback. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Stoffer Department of Statistics University of Pittsburgh Pittsburgh, Pennsylvania USA Shumway Department of Statistics University of California Davis, California USA

Time Series Analysis and Its Applications With R Examples Third edition Olkinįor other titles published in this series, go to Robert H. Springer Texts in Statistics Series Editors G.

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