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Introduction to Time Series and Forecasting (Springer Texts in Statistics) 3rd ed. 2016 Edition
Purchase options and add-ons
The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Many additional special topics are also covered.
New to this edition:
- A chapter devoted to Financial Time Series
- Introductions to Brownian motion, Lévy processes and Itô calculus
- An expanded section on continuous-time ARMA processes
- ISBN-109783319298528
- ISBN-13978-3319298528
- Edition3rd ed. 2016
- PublisherSpringer
- Publication dateAugust 31, 2016
- LanguageEnglish
- Dimensions8.46 x 1.1 x 11.45 inches
- Print length439 pages
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Editorial Reviews
Review
From the Back Cover
The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Many additional special topics are also covered.
New to this edition:
- A chapter devoted to Financial Time Series
- Introductions to Brownian motion, Lévy processes and Itô calculus
- An expanded section on continuous-time ARMA processes
From reviews of the first edition:
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This book, like a good science fiction novel, is hard to put down.… Fascinating examples hold one’s attention and are taken from an astonishing variety of topics and fields.… Given that time series forecasting is really a simple idea, it is amazing how much beautiful mathematics this book encompasses. Each chapter is richly filled with examples that serve to illustrate and reinforce the basic concepts. The exercises at the end of each chapter are well designed and make good use of numerical problems. Combined with the ITSM package, this book is ideal as a textbook for the self-study student or the introductory course student. Overall then, as a text for a university-level course or as a learning aid for an industrial forecaster, I highly recommend the book. –SIAM Review
In addition to including ITSM, the book details all of the algorithms used in the package―a quality which sets this text apart from all others at this level. This is an excellent idea for at least two reasons. It gives the practitioner the opportunity to use ITSM more intelligently by providing an extra source of intuition for understanding estimation and forecasting, and it allows the more adventurous practitioners to code their own algorithms for their individual purposes.… Overall I find Introduction to Time Series and Forecasting to be a very useful and enlightening introduction to time series. –Journal of the American Statistical Association
The emphasis is on hands-on experience and the friendly software that accompanies the book serves the purpose admirably.… The authors should be congratulated for making the subject accessible and fun to learn. The book is a pleasure to read and highly recommended. I regard it as the best introductory text in town. –Short Book Reviews, International Statistical Review
About the Author
Peter J. Brockwell and Richard A. Davis are Fellows of the American Statistical Association and the Institute of Mathematical Statistics and elected members of the International Statistics institute. Richard A. Davis is the current President of the Institute of Mathematical Statistics and, with W.T.M. Dunsmuir, winner of the Koopmans Prize. Professors Brockwell and Davis are coauthors of the widely used advanced text, Time Series: Theory and Methods, Second Edition (Springer-Verlag, 1991).
Product details
- ASIN : 3319298526
- Publisher : Springer; 3rd ed. 2016 edition (August 31, 2016)
- Language : English
- Hardcover : 439 pages
- ISBN-10 : 9783319298528
- ISBN-13 : 978-3319298528
- Item Weight : 3.42 pounds
- Dimensions : 8.46 x 1.1 x 11.45 inches
- Best Sellers Rank: #441,150 in Books (See Top 100 in Books)
- #91 in Econometrics & Statistics
- #460 in Statistics (Books)
- #719 in Probability & Statistics (Books)
- Customer Reviews:
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With piles of statistics books stacked on shelf, I purchased this one to get some further understanding in forecasting techniques, and found myself totally lost. It might be a useful as text book if you can fully rely on your teacher. But definitely not a good choice for self study.
By the way, for those who want to get some "introduction" to the forecasting and time series models, try Forecasting Methods and Applications by Makridakis. Although 20 years old it is still much better as a newbie guide.
Furthermore, the problems are generally very, very difficult to parse and work out. There aren't easier problems before ramping up to harder ones like I've seen in other statistics textbooks. Not having easier problems poses a big issue with such an unwieldy book is a big issue as you cannot easily use them to assist in deciphering the text.
The one thing that I did appreciate from the book was the R Code excerpts, which are generally able to be understood without too much trouble. As such, the book will probably have a place to live on my shelf, but it will not be what I would reference in the future when I need to remember stuff about Time Series.
Top reviews from other countries
Publish should reconsider this, this is not a fiction book which can be read at leisure on mobile. This needs to be read and understood like text book.