Time Series Analysis: With Applications in R

by Jonathan D. Cryer, Kung-Sik Chan

Time Series Analysis With Applications in R, Second Edition, presents an accessible approach to understanding time series models and their applications. Although the emphasis is on time domain ARIMA models and their analysis, the new edition devotes two chapters to the frequency domain and three to time series regression models, models for heteroscedasticity, and threshold models. All of the ideas and methods are illustrated with both real and simulated data sets.

A unique feature of this edition is its integration with the R computing environment. The tables and graphical displays are accompanied by the R commands used to produce them. An extensive R package, TSA, which contains many new or revised R functions and all of the data used in the book, accompanies the written text. Script files of R commands for each chapter are available for download. There is also an extensive appendix in the book that leads the reader through the use of R commands and the new R package to carryout the analyses.

Genres: Nonfiction, Textbooks

505 pages, Hardcover

First published April 4, 2008

Reviews

[Anurag · Rating 4 out of 5]

It's not a great treatise on theory but a good way to get comfortable with time-series modeling in R. I feel there are a lot of functions in R that should have been explained better in the beginning but the authors seem more interested in developing the intuition instead. I won't recommend reading this as the only book on time-series analysis but rather as a practice book with another more theoretical text.

[Dwi Nur'Aini Putri · Rating 4 out of 5]

Theoretical quite hard to understand but practically well enough to applied in R.