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Showing 1-10 of 15 reviews(Verified Purchases). See all 32 reviews
on October 12, 2016
This book is heavy on theory and formulas. If you are not PhD in math, you will probably have difficulties following some of the concepts.
Even though the authors claim that the book has practical examples in R, the book is mostly theoretical. Most of the formulas are not explained and you will end up guessing what "k", "j", and hundreds of other Greek letters and symbols mean. Most of the time series topics do not have any numerical examples and for each sentence you will end up staring at 5 different formulas. Later, you will end up Googling stuff. The good side of the book is that it includes the most important time series theoretical concepts and it is useful to have this book if you are serious about time series analysis.
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on August 5, 2016
I used this in a graduate level course and found the structure of the subjects useful and the addition of R syntax marginally synthetic, particularly in appendices. However, many of the topics covered in chapter exercises include tasks in following chapters; this is NOT useful! Additionally, some of the syntax used in Exhibits are inconclusive and only marginally helpful e.g. incomplete script [clearly a editorial oversight]. When prescribing to this text be prepared to use Cran's R directories references for assistance; R proficiency dependent. This is a sound text likely as supplemental material but not exclusively.
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on August 31, 2016
This book makes heavy use of mathematical proofs in the early chapters to make make its points. This may suit some readers and not suit others. The early chapters describe the core principles.

If you're a person who likes narrative descriptions rather than mathematical proofs, then this book probably isn't for you. If you're a person who doesn't mind mathematical proofs as long as there's a lot of hand-holding explanations of the proofs, then this book is probably not for you, either.

If you're okay with mathematical proofs, then this book is probably okay for you.
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on August 14, 2015
Just what I needed for my class!
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on May 18, 2010
Very well written, easy to understand. But it is a basic/elementary textbook. If I were learning time series on my own and wanted to use the R language, I would read this book first.
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on October 9, 2015
As described
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on October 11, 2015
great!
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on August 25, 2011
This is the text book for my STAT 478, Statistical Forecasting, at Northern Illinois University. The semester is just starting, but Amazon requested a review.

The nice thing about this text is its examples using R (an open-source statistics program). R is a free program which is nicer for a student than a commercial program like SAS. As an added bonus, there is a package for R called TSA (Time Series Analysis) which was developed by the Authors and has supporting data to compliment the text.

Its an older publication, so the cost of learning for this book and program is low, which should be good for a student or interested party on a budget.
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on October 8, 2015
No surprises, and got it in just 10 days (from US to Europe). Great.
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on April 23, 2015
Good book a little dry but great content.
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