Time Series: Data Analysis and Theory (Classics in Applied Mathematics No. 36)

Time Series: Data Analysis and Theory (Classics in Applied Mathematics No. 36)

By: David R. Brillinger (author), Robert O'Malley (series_editor)Paperback

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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.

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Preface; 1. The nature of time series and their frequency analysis; 2. Foundations; 3. Analytic properties of Fourier transforms and complex matrices; 4. Stochastic properties of finite Fourier transforms; 5. The estimation of power spectra; 6: Analysis of a linear time invariant relation between a stochastic series and several deterministic series; 7. Estimating the second-order spectra of vector-valued series; 8. Analysis of a linear time invariant relation between two vector-valued stochastic series; 9. Principal components in the frequency domain; 10. The canonical analysis of time series; Proofs of theorems; References; Notation index; Author index; Subject index; Addendum.

Product Details

  • publication date: 01/09/2001
  • ISBN13: 9780898715019
  • Format: Paperback
  • Number Of Pages: 570
  • ID: 9780898715019
  • weight: 719
  • ISBN10: 0898715016

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