Time Series: Data Analysis and Theory
By addebook • Nov 20th, 2008 • Category: Mathematics •
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Time Series: Data Analysis and Theory (Classics in Applied Mathematics, 36) (Classics in Applied Mathematics)
by David R. Brillinger
Time Series: Data Analysis and Theory (Classics in Applied Mathematics, 36) (Classics in Applied Mathematics)
By David R. Brillinger
Publisher: SIAM: Society for Industrial and Applied Mathematics
Number Of Pages: 540
Publication Date: 2001-09-01
ISBN-10 / ASIN: 0898715016
ISBN-13 / EAN: 9780898715019
Binding: Paperback
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.
Summary: good text from the expert on frequency domain time series
Rating: 5
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.
Summary: A wonderful book
Rating: 5
I think this is not an introductory book to the spectral analysis of time series. But, once you have taken a first course on time series, this is a wonderful and useful book.
Summary: Still the best monograph on frequency domain analysis of sta
Rating: 5
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!
Summary: rigorous treatment of frequency domain analysis
Rating: 4
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.
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