- Hardcover: 784 pages
- Publisher: Wiley; 4 edition (June 30, 2008)
- Language: English
- ISBN-10: 0470272848
- ISBN-13: 978-0470272848
- Product Dimensions: 6.4 x 1.6 x 9.5 inches
- Shipping Weight: 2.6 pounds (View shipping rates and policies)
- Average Customer Review: 3.4 out of 5 stars See all reviews (10 customer reviews)
- Amazon Best Sellers Rank: #1,160,525 in Books (See Top 100 in Books)
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Time Series Analysis: Forecasting and Control 4th Edition
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?The book follows faithfully the style of the original edition. The approach is heavily motivated by real world time series, and by developing a complete approach to model building, estimation, forecasting and control.? (Mathematical Reviews, 2009)
"I think the book is very valuable and useful to graduate students in statistics, mathematics, engineering, and the like. Also, it could be of tremendous help to practioners. Even though the book is written in a clear, easy to follow narrative style with plenty of illustrations, one should nevertheless have a sufficient knowledge of graduate level mathematical statistics. By reading and understanding the book one should, in the end, feel very confident in time series and analysis." (MAA Reviews, January 13, 2009)
"I think the book is very valuable and useful to graduate students in statistics, mathematics, engineering, and the like. Also, it could be of tremendous help to practioners. Even though the book is written in a clear, easy to follow narrative style with plenty of illustrations, one should nevertheless have a sufficient knowledge of graduate level mathematical statistics. By reading and understanding the book one should, in the end, feel very confident in time series and analysis." (MAA Reviews, January 2009)
From the Publisher
This is a complete revision of a classic, seminal, and authoritative text that has been the model for most books on the topic written since 1970. It explores the building of stochastic (statistical) models for time series and their use in important areas of application --forecasting, model specification, estimation, and checking, transfer function modeling of dynamic relationships, modeling the effects of intervention events, and process control. --This text refers to an alternate Hardcover edition.
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Top Customer Reviews
2nd UPDATE: Found an even better resource. "A Practical Guide to Box - Jenkins Forecasting" by John C. Hoff. Also useful has been "Applied Data Mining for Forecasting Using SAS" by Rey, Kordon, and Wells.
Gwilym Jenkins died many years prior to this edition and Box's colleague Greogory Reinsel took on the task of helping to revise and update it.
It retains its original flavor. It is an applied book with many practical and illustrative examples. It concentrates on the three stages of time series analysis: modeling building, selection, estimation and diagnostic checking and how to iterate the process toward a good solution. The ARIMA time series models are what are considered. The theory of stationary and nonstationary time series is introduced to motivate interpretation of autocorrelation and partial autocorrelation in the model identification phase. Operator notation is introduced and used throughout the book to simplify equations. For me it helped simplify things and illuminate some concepts. But many readers found it difficult and confusing. the book is very systematic and practical. Many of the examples are real examples from Box's work in the chemical industry and his consulting during his career at the University of Wisconsin and also the consulting experience of Gwilym Jenkins in England.
The publishers and some amazon reviewers say that this edition is a major revision. The second edition published in 1976 was criticized for being essentially a reprint of the first. Although there is a new chapter 12 on intervention analysis and outlier detection it mainly is an expansion of ideas already discussed in the first edition. Theoretical results are kept aside in appendices as in previous editions.
This is not an up-to-date text on the theory of time series. It deals strictly with the time domain approach and does not include recent advances including nonlinear and bilinear models, models with non-Gaussian innovations and bootstrap or other resampling methods.
To get a balanced approach that includes the theory for frequency and time domain approaches the book by Shumway, the latest edition of the Brockwell and Davis text and the latest edition of Fuller's text are appropriate. For a graduate course I taught at UC Santa Barbara in 1981 I used the first edition of Fuller's book. Anderson provides a thorough account of the time domain theory. Excellent texts that specialize in the frequency domain approach are Bloomfield's second edition and the two volume book by Priestley. Brillinger's text is also worthwhile for those interested in spectral theory (frequency domain statistics).
Although there are many things that is text does not cover, it remains the classical text on a rich class of time domain methods that are still very practical. This is a text I bought for reference even though I still have the first edition.