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Summary:
Time Series: Theory and Methods is a systematic account of linear time series models and their application to the modelling and prediction of data collected sequentially in time. The aim is to provide specific techniques for handling data and at the same time to provide a thorough understanding of the mathematical basis for techniques. Both time and frequency domain methods are discussed, but the book is written in such a way that either approach could be emphasized. The book intended to be a text for graduate students in statistics, mathematics, engineering, and the natural or social sciences. It contains substantial chapters on multivariate series and state-space models (including applications of the Kalman recursions to missing-value problems) and shorter accounts of special topics including long-range dependence, infinite variance processes and non-linear models. Most of the programs used in the book are available on diskettes for the IBM-PC. These diskettes, ! with the accompanying manual, ITSM: The Interactive Time Series Modelling Package for the PC, also by Brockwell and Davis, can be purchased from Springer-Verlag.
Customer Reviews:
Average Customer Rating:
Great book
Customer Rating:
I reviewed this book once before under the pen name statman13. So look at that review to get most of my thoughts about it. I taught times series analysis as a graduate course at UC Santa Barbara many years ago. That was long before this book came out. I used Wayne Fuller's book as a text because it had balanced coverage of time domain and frequency domain approaches. If I were to do it over today I would use Brockwell and Davis' book as it has the right level of theory and also a proper mix of frequency and time domain. I know Richard Davis to be an excellent probabilist and very knowledgeable about stochastic process. I collaborated with him on a paper in extreme value theory. I also had the privilege of refereeing one of his early papers on extreme values that was part of his disseration and was eventually published in the Annals of Probability.
Time Series: Theory and Methods
Customer Rating:
Excellent reading. This book covers mainly the frequentist approach to time series analysis in a very informative way. The book starts off by introducing Hilbert spaces, then moves to stationary ARMA processes and so on. My favourite is chapter 10, Inference for the Spectrum of a Stationary Process, in which different tests are considered for periodicities at known and unknown frequencies.
Rigorous, difficult, but feasible
Customer Rating:
Of course, this an advanced textbook on Time Series. The reader is supposed to have been introduced to the subject, and certainly is looking for a more theoretical treatment.
If you want to learn time series for the first time, this is not the book.
If you want a friendly book, do not see springer's publications.
However, if you want a fair rigourous book, you have found it.
I think the exercises are illustrative, but sometimes long.
excellent and rigorous treatment of time series methods
Customer Rating:
This text provides a thorough treatment of the time and frequency domain theory for time series data. It provides a rigorous and theoretical treatment. This is a graduate level text for statistics majors. It provides good coverage of ARIMA models. There are also a number of other good texts on time series analysis both theoretical and applied. Some like Koopmans' text and Bloomfield's emphasize the frequency domain and others like Box, Jenkins and Reinsel the time domain. Another excellent recent text is the one by Shumway and Stoffer. Chatfield's monograph provides a concise elementary introduction.
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