Introduction to Time Series and Forecasting

Abstract

Thisbookisaimedatthereaderwhowishestogainaworkingknowledgeoftimeseries and forecasting methods as applied in economics, engineering, and the natural and social sciences. Unlike our more advanced book, Time Series: Theory and Methods, Brockwell and Davis (1991), this one requires only a knowledge of basic calculus, matrix algebra and elementary statistics at the level, for example, of Mendenhall et al. (1990). It is intended for upper-level undergraduate students and beginning graduate students. Theemphasisisonmethodsandtheanalysis ofdatasets.Theprofessional version of the time series package ITSM2000, for Windows-based PC, enables the reader to reproduce most of the calculations in the text (and to analyze further data sets of the reader’s own choosing). It is available for download, together with most of the data sets used in the book, from http://extras.springer.com. Appendix E contains a detailed introduction to the package. Verylittlepriorfamiliaritywithcomputingisrequiredinordertousethecomputer package. The book can also be used in conjunction with other computer packages for handling time series. Chapter 14 of the book by Venables and Ripley (2003) describes howtoperform manyofthecalculations using SandR.Thepackage ITSMRofWeigt (2015) can be used inR toreproduce many ofthe features ofITSM2000. Thepackage Yuima, also for R, can be used for simulation and estimation of the Lévy-driven CARMA processes discussed in Section 11.5 (see Iacus and Mercuri (2015)). Both of these packages can be downloaded from https://cran.rproject.org/web/packages. There are numerous problems at the end of each chapter, many of which involve use of the programs to study the data sets provided.