Time series : data analysis and theory /

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Bibliographic Details
Author / Creator:	Brillinger, David R.
Imprint:	Philadelphia, Pa. : Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104), 2001.
Description:	1 online resource (xx, 540 pages : illustrations) : digital file
Language:	English
Series:	Classics in applied mathematics ; 36 Classics in applied mathematics ; 36.
Subject:	Time-series analysis. Fourier transformations. Fourier transformations. Time-series analysis.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/12577173

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Other authors / contributors:	Society for Industrial and Applied Mathematics.
ISBN:	9780898719246 0898719240 9780898715019 0898715016
Notes:	"This SIAM edition is an unabridged republication of the work first published by Holden Day, Inc., San Francisco, 1981"--Title page verso. Includes bibliographical references. Restricted to subscribers or individual electronic text purchasers. Also available in print version. Title page of print version.
Summary:	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. Audience: this book will be most useful to applied mathematicians, communication engineers, signal processors, statisticians, and time series researchers, both applied and theoretical. Readers should have some background in complex function theory and matrix algebra and should have successfully completed the equivalent of an upper division course in statistics.
Other form:	Print version: Brillinger, David R. Time series. Philadelphia : Society for Industrial and Applied Mathematics, ©2001 0898715016
Publisher's no.:	CL36 siam

Table of Contents:

The nature of time series and their frequency analysis
Foundations
Analytic properties of Fourier transforms and complex matrices
Stochastic properties of finite Fourier transforms
The estimation of power spectra
Analysis of a linear time invariant relation between a stochastic series and several deterministic series
Estimating the second-order spectra of vector-valued series
Analysis of a linear time invariant relation between two vector-valued stochastic series
Principal components in the frequency domain
The canonical analysis of time series
Proofs of theorems
Addendum: Fourier analysis of stationary processes.

Time series : data analysis and theory /

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