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

The book is OK but it falls behind other available texts at comparable or lower prices. I agree with others that the book is not the best introduction and neither a must-have rigorous reference. The main contribution is that it does account for some topics not typically found in most time series textbooks as mentioned in Dr. Chernick's review. The new edition of the classic by Box et al and the introductory text by Brockwell and Davis (ITSF) are muchl superior to Shumway and Stoffer in terms of introducing the core subject (ARIMA modelling) though not using R. If one wants R material (which by the way has powerful time series resources) than the book by Cryer and Chan does a much better job. If one wants more theory and technical detail, and also a solid introduction to multivariate methods, then the theoretical book by Brockwell and Davis (TSTM) and Hamilton's text are way better than this book. Applied economists wanting intro material should check Ender's applied text and engineers serious about time series cannot do better than owning Box et al and the (frequency domain) book by Percival and Walden. Statisticians and advanced readers can go to the two theoretical books I mentioned before.

As mentioned by some other reviewers, this book may be a good book in content, but it is very badly organized. The author references figures or equations from everywhere in the book. You have to go through chapters back and forth. Some important definitions are not clearly defined. They were just written into normal passages.

First of this book has a lot of useful information and is quite accessible. Some graduate level math is required, but you should have this anyways if you want to do time series analysis. There is a free version of this book online, which triggered my purchase. It mostly uses R functions in the TSA package, which is also written by the author.Now when I got to the point when I wanted to estimate a GARCH + ARIMA model, I got really disappointed. The author does do this in the book, but uses SAS since SAS allows for Nelson Cao inequality constraints in the model. Non of the readers are likely to have access to SAS, are willing to pay for it, or want to learn how to use it. This screams for an updated version of the book as well as the TSA package that does allow for estimating an GARCH + ARIMA model in R, something very common in financial markets. The rugarch package in R has this functionality, although I am not sure if it takes Nelson - Cao inequality constraints into account and how bad it is if it does not. I suspect that in a somewhat stable model these constraints are probably not binding, but this is all not covered in this book.

An absolutely catastrophic mix of ambiguous notation, muddled exposition and doubtful structure. The book frequently skips from one equation to the next with little or no explanation, and seems to routinely generalise from simple cases to more complicated ones without explanation or justification. Needless to say, it also lacks rigour in a most deplorable way.

Fist off, what this book is not: It is not a Time Series Theory book like Tsay or Brockwell. If all you want is mathematical rigor, go somewhere else.Now, as to what the book is: it is an very easy to read intermediate text with examples drawn from the real world. It is also reasonably complete in building programming examples in R (with exception of Chapter 7, lamentably ... Chapter 6 code is available on the book's website).One other reviewer commented that some of the examples consist of only one line of R code. This is part of the power of R and CRAN that such powerful statistical techniques like ARIMA and Factor Modeling can be represented in a single function call, and not a shortcoming of the book.This book will not replace Tsay or Zivot and Wang on my shelf, but is an accesible, excellent text that does a very good job of covering its intended purpose, including some relatively advanced topics. Publishing code for Chapter 7 would rate this book its fifth star.

I like this book especially because it has good examples of R code that can be used. However in general, I think this book is very theoretical for a beginner who just wants to learn about time series. Reading this book requires prior knowledge about time series.

While Enders remains the most popular book for those who are taking a time series class. I highly recommend this book as an advanced reference on the subject regardless of your research area. Shumway divides the book into basic, involved and finally advanced topics. He then subdivides these sections into time and frequency based time series. The result is a book that gives a very comprehensive review of all time series methods.A greater plus for this book is that it introduces time series methods in R, and what packages one can use to perform time series analysis using the ever popular stats language. However, as an earlier reviewer has pointed out, the book does not go into a step by step walk through the packages, but rather gives enough information that a reader can easily look through CRAN to find more information on the exact workings of the packages and functions described within.Over all, a must have for the bookshelf

Time Series Analysis and Its Applications: With R Examples is well-written and packaged good. Nice book with reasonable price, wonderful reference for Stat courses time series analysis. Thank you so much!

This book is amazing. very clear and easy to follow compared with other books. I have no background in time series but after reading and doing questions in the book i can apply time series models to real data. This book has a lot of formula but most of them could be figure out if you give time and thought. I will highly recommend this for self-study. chapter 1 to 10 are the basic time series and should be sufficient for most of the cases in work.

Muy bien explicado, arima, arch y garch, 100% practico

ottimo testo per l'argomento relatio, spedizione nei tempi previsti, acquisto consigliato

Not as accessible as the author would like to beleive. Difficult read.

Arrived on time and quality was exactly as mentioned in the description.