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9780898715019 Academic Inspection Copy

Time Series

Data Analysis and Theory
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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.
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.
This text employs basic techniques of univariate and multivariate statistics for the analysis of time series and signals.
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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