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Time Series: Data Analysis and Theory: 36 (Classics in Applied Mathematics, Series Number 36) - Softcover
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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'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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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. An extensive set of original exercises is included.
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- PublisherSociety for Industrial and Applied Mathematics
- Publication date2001
- ISBN 10 0898715016
- ISBN 13 9780898715019
- BindingPaperback
- Number of pages570
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Time Series: Data Analysis and Theory (Classics in Applied Mathematics, Series Number 36)
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