Foundations of Time Series Analysis and Prediction Theory
Language: English
Published by Wiley-Interscience, 2001
- First Edition
- Hardcover
- Used
Seller: SoCo Books, Trinidad, CO, U.S.A.SoCo Books
AbeBooks seller since November 5, 2025
Condition: Used - Fine
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Preface says that this "book provides a solid foundation for time series analysis and prediction theory . interdisciplinary nature of time series analysis lying at the intersection of the mathematical, statistical, computational, physical, engineering and system sciences. The goal is to join the two lines of developments in time series analysis centered around the work of Schuster, Yule, Slutsky, Wold, . and prediction theory base on the work of Szego, Wold, Cramer, Kolmororov, Wiener, . into a logically sound and pedagogically reasonable theory of modern statistical time series analysis.".
Seller Inventory # 76803
- Title
- Foundations of Time Series Analysis and Prediction Theory
- Author
- Pourahmadi, Mohsen
- Publisher
- Wiley-Interscience
- Publication year
- 2001
- Condition
- Fine
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0471394343
- ISBN 13
- 9780471394341
- Edition
- 1st Edition
- Item weight
- 1.649 pounds
- Dimensions
- 1.02 inches width by 6.26 inches height by 9.53 inches depth
This volume provides a mathematical foundation for time seriesanalysis and prediction theory using the idea of regression and thegeometry of Hilbert spaces. It presents an overview of the tools oftime series data analysis, a detailed structural analysis ofstationary processes through various reparameterizations employingtechniques from prediction theory, digital signal processing, andlinear algebra. The author emphasizes the foundation and structureof time series and backs up this coverage with theory andapplication.
End-of-chapter exercises provide reinforcement for self-study andappendices covering multivariate distributions and Bayesianforecasting add useful reference material. Further coveragefeatures:
* Similarities between time series analysis and longitudinal dataanalysis
* Parsimonious modeling of covariance matrices through ARMA-likemodels
* Fundamental roles of the Wold decomposition andorthogonalization
* Applications in digital signal processing and Kalmanfiltering
* Review of functional and harmonic analysis and predictiontheory
Foundations of Time Series Analysis and Prediction Theory guidesreaders from the very applied principles of time series analysisthrough the most theoretical underpinnings of prediction theory. Itprovides a firm foundation for a widely applicable subject forstudents, researchers, and professionals in diverse scientificfields.
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SoCo Books
Trinidad, CO, U.S.A.
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