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Business Intelligence Books - SAS for Forecasting Time Series, Second Edition
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List Price: $63.95
Our Price: $57.55
Your Save: $ 6.40 ( 10% )
Availability: Usually ships in 24 hours
Manufacturer: SAS Publishing
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Average Customer Rating:  
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Binding: Paperback
Dewey Decimal Number: 004
EAN: 9781590471821
ISBN: 1590471822
Label: SAS Publishing
Manufacturer: SAS Publishing
Number Of Items: 1
Number Of Pages: 420
Publication Date: 2003-04-18
Publisher: SAS Publishing
Studio: SAS Publishing
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Editorial Reviews:
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In this second edition of the indispensable SAS for Forecasting Time Series, Brocklebank and Dickey show you how SAS performs univariate and multivariate time series analysis. Taking a tutorial approach, the authors focus on the procedures that most effectively bring results: the advanced procedures ARIMA, SPECTRA, STATESPACE, and VARMAX. They demonstrate the interrelationship of SAS/ETS procedures with a discussion of how the choice of a procedure depends on the data to be analyzed and the results desired. With this book, you will learn to model and forecast simple autoregressive (AR) processes using PROC ARIMA, and you will learn to fit autoregressive and vector ARMA processes using the STATESPACE and VARMAX procedures. Other topics covered include detecting sinusoidal components in time series models, performing bivariate cross-spectral analysis, and comparing these frequency-based results with the time domain transfer function methodology. New and updated examples in the second edition include retail sales with seasonality, ARCH models for stock prices with changing volatility, vector autoregression and cointegration models, intervention analysis for product recall data, expanded discussion of unit root tests and nonstationarity, and expanded discussion of frequency domain analysis and cycles in data.
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Spotlight customer reviews:
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Customer Rating:
Summary: Too redundant!!!
Comment: I had hoped that it would turn out to be at least a good book (if not excellent) by seeing such big names in the list of authors but am terribly disappointed! The table which normally could have been printed in a fraction of page has been printed on a complete page. Even if that was not enough, 5-6 pages continuously filled with 5-6 tables (all displaying the same meaning) can be commonly seen throughout the book. There is a terrible amount of repetition in printed matter also.
It seems (though might be unintentionally) that a lot of stress has been given to enhance the page count of the book while giving almost no consideration to the quality of the material.
In addition, a lot of important matter (for example non-linear time series models) have just not been covered.
Customer Rating:
Summary: Value added < 0
Comment: .. the benchmark being SAS/ETS documentation, to which, I am sure, the authors themselves have contributed. Let me just recommend making a print-out of selected chapters of SAS/ETS User's Guide - available online - describing the procedures that you (may) need, such as MODEL, FORECAST, ARIMA, VARMAX, UTC and STATESPACE.
Customer Rating:
Summary: Ugh!
Comment: The SAS Institute's Books by Users series contains many excellent manuals. The ones by Paul Allison (on survival analysis and on logistic regression) and by Stokes, Davis and Koch (categorical data analysis) are particularly well-written and illuminating. Unfortunately, Brocklebank and Dickey's contribution on time series analysis falls far short of the mean.
The problem is not the statistical content, which is quite reliable, but rather than explanatory style. Chapters are disorganized, with many ideas introduced before being explained. Furthermore, the authors have adopted an unfortunate habit of constantly referring to "you" (i.e., the reader). "You" will do this. "You" will decide to do that. In many case, it was far from clear why such decisions would be made.
The most serious problem, though, is the treatment of SAS code. This is supposed to be a book about ideas AND about syntax. But code is repeatedly presented with any kind of line-by-line explantion. Readers ("you" again) are left to wonder what the various elements of code mean, and how they control the computations done.
I was very disappointed with this book. Unfortunately, the only alternative is to use the SAS documentation, and that's not really a very good alternative.
Customer Rating:
Summary: Excellent
Comment: If you're interested in advanced methods of forecasting time series data using SAS then this is the book to have. It is loaded with examples and interpretation of output as well as a nice concise explanation of theory. Everything you would expect from such renowned authors.
Customer Rating:
Summary: This manual needs a chapter on forecast accuracy.
Comment: While the publishers describe SAS for Forecasting Time Series as a manual, the authors have provided more than SAS statements and the resulting outputs. Theoretical explanations, equations, and matrix algebra forms of equations fill the book. This superb manual is the product of the Research and Development Director of Analytic Solutions at SAS and of the Professor of Statistics who was the co-inventor of the Dickey-Fuller test. In addition to the coverage of the essential univariate and multivariate time series analysis topics (e.g., ARIMA models), the authors included entire chapters or large portions of chapters on: Cointegration, State Space Modeling, Spectral Analysis, and Data Mining.
My only disappointment with this manual was the lack of an entire chapter on forecast accuracy. Four pages of references did not include a single reference to articles about forecasting competitions. The authors could have: (1) held back recent data in their examples (2) made forecasts with their best models (3) explained how to identify significant changes over time in error terms, standard errors, and in correlations (4) explained when and how to re-calculate model parameters (5) discussed the choice of unbiased forecast accuracy measures for comparing forecasts from ARIMA and regression models.
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