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Time Series: Data Analysis and Theory (Classics in Applied Mathematics, 36), by David R. Brillinger
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Intended for students and researchers, this text employs basic techniques of univariate and multivariate statistics for the analysis of time series and signals. It provides a broad collection of theorems, placing the techniques on firm theoretical ground. The techniques, which are illustrated by data analyses, are discussed in both a heuristic and a formal manner, making the book useful for both the applied and the theoretical worker. An extensive set of original exercises is included. Time Series: Data Analysis and Theory takes the Fourier transform of a stretch of time series data as the basic quantity to work with and shows the power of that approach. It considers second- and higher-order parameters and estimates them equally, thereby handling non-Gaussian series and nonlinear systems directly. The included proofs, which are generally short, are based on cumulants.
- Sales Rank: #773125 in Books
- Brand: Brand: SIAM: Society for Industrial and Applied Mathematics
- Published on: 2001-09
- Original language: English
- Number of items: 1
- Dimensions: 8.98" h x 1.10" w x 5.98" l, 1.70 pounds
- Binding: Paperback
- 540 pages
- Used Book in Good Condition
Review
'Intended for students and researchers, this text employs basic techniques of univariate and multivariate statistics for the analysis of time series and signals. It covers a broad collection of theorems. The techniques are illustrated by data analyses and are discussed both heuristically and formally to serve both the applied and the theoretical worker.' IEEE Signal Processing Magazine
About the Author
David R. Brillinger is a Professor in the Department of Statistics at the University of California, Berkeley, and is also chair of the Bernoulli Society's Committee on Probability and Statistics in the Physical Sciences. A native Canadian, he is President of the Statistical Society of Canada for the year 2001-2002. Dr. Brillinger is the recipient of many awards in mathematics and statistics, has edited and served on the editorial boards of several distinguished journals, and is a frequent invited lecturer.
Most helpful customer reviews
24 of 25 people found the following review helpful.
good text from the expert on frequency domain time series
By Michael R. Chernick
Brillinger's book gives a thorough and advanced treatment of the frequency domain approach to time series analysis. It is more rigorous and advanced than Bloomfield but is not as easy to read and understand. It is the only text that I know of, to illustrate the power of the complex normal distribution as first suggested by N. Roy Goodman. Besides the interesting and rigorous treatment another nice feature of the book is the data analytic approach to many real time series.
15 of 15 people found the following review helpful.
Still the best monograph on frequency domain analysis of sta
By prof.dr. P.C.M. Molenaar
Brillinger's book is unsurpassed in its thorough and transparent treatment of frequency domain analysis of weakly stationary time series (continuous state - discrete time). It generalizes all standard multivariate statistical analysis techniques (regression analysis, analysis of variance, principal component analysis, etc.) to the setting of weakly stationary series and presents detailed discussions of the associated sampling distributions. It is my preferred source for looking up such things as the sampling distribution of estimated coherency, estimated phase spectrum, etc. An excellent book!
0 of 0 people found the following review helpful.
A must-have for time series econometricians who do work in spectral domain
By General Specific
A very comprehensive book for those of us who find themselves shifting to spectral domain from time domain. Contains tons of useful lemmas and results and can make a real difference when constructing a proof.
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