UID:
almahu_9947357903402882
Format:
1 electronic text (xx, 540 p.) :
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ill., digital file.
ISBN:
9780898719246 (electronic bk.)
Series Statement:
Classics in applied mathematics ; 36
Content:
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.
Note:
"This SIAM edition is an unabridged republication of the work first published by Holden Day, Inc., San Francisco, 1981"--T.p. verso.
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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.
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Also available in print version.
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Mode of access: World Wide Web.
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System requirements: Adobe Acrobat Reader.
Additional Edition:
Print version: ISBN 0898715016
Additional Edition:
ISBN 9780898715019
Language:
English
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