Multidimensional Stationary Time Series: Dimension Reduction and PredictionКНИГИ » НАУКА И УЧЕБА
Название: Multidimensional Stationary Time Series: Dimension Reduction and Prediction Автор: Marianna Bolla, Tamas Szabados Издательство: Chapman and Hall/CRC Год: 2021 Страниц: 296 Язык: английский Формат: pdf (true) Размер: 10.1 MB
This book gives a brief survey of the theory of multidimensional (multivariate), weakly stationary time series, with emphasis on dimension reduction and prediction. Understanding the covered material requires a certain mathematical maturity, a degree of knowledge in probability theory, linear algebra, and also in real, complex and functional analysis. For this, the cited literature and the Appendix contain all necessary material. The main tools of the book include harmonic analysis, some abstract algebra, and state space methods: linear time-invariant filters, factorization of rational spectral densities, and methods that reduce the rank of the spectral density matrix.
- Serves to find analogies between classical results (Cramer, Wold, Kolmogorov, Wiener, Kalman, Rozanov) and up-to-date methods for dimension reduction in multidimensional time series. - Provides a unified treatment for time and frequency domain inferences by using machinery of complex and harmonic analysis, spectral and Smith--McMillan decompositions. Establishes analogies between the time and frequency domain notions and calculations. - Discusses the Wold's decomposition and the Kolmogorov's classification together, by distinguishing between different types of singularities. Understanding the remote past helps us to characterize the ideal situation where there is a regular part at present. Examples and constructions are also given. - Establishes a common outline structure for the state space models, prediction, and innovation algorithms with unified notions and principles, which is applicable to real-life high frequency time series.
It is an ideal companion for graduate students studying the theory of multivariate time series and researchers working in this field.
This book offers comprehensive coverage of the most essential topics, including:
Treating processes, materials, system applications related to fuzzy logic Highlighting new areas of application of fuzzy logic Identifying possibilities of much wider applications of fuzzy logic Modeling of sustainability with the help of fuzzy logic
The level enables a selection of the text to be made for the substance of undergraduate-, graduate-, and postgraduate-level courses. There is also sufficient volume and quality for the basis of a postgraduate course. A more restricted and judicious selection can provide the material for a professional short course and various university-level courses.
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Multidimensional Stationary Time Series: Dimension Reduction and Prediction 
Название: Multidimensional Stationary Time Series: Dimension Reduction and Prediction
