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Time Series

Time Series
Data Analysis and Theory

£63.00

Part of Classics in Applied Mathematics

  • Date Published: September 2001
  • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
  • format: Paperback
  • isbn: 9780898715019

£ 63.00
Paperback

This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
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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.

    • Most useful to applied mathematicians, communication engineers, signal processors, statisticians and time series researchers, both applied and theoretical
    • Readers should have some background knowledge in complex function theory and matrix algebra and should have successfully completed the equivalent of an upper division course in statistics
    • An extensive set of original exercises is included
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    Reviews & endorsements

    '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

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    Product details

    • Date Published: September 2001
    • format: Paperback
    • isbn: 9780898715019
    • length: 570 pages
    • dimensions: 228 x 152 x 28 mm
    • weight: 0.719kg
    • availability: This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
  • Table of Contents

    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.

  • Author

    David R. Brillinger, University of California, Berkeley

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