The book provides the foundation of time series methods, including linear filters and a geometric approach to prediction. The important paradigm of ARMA models is studied in-depth, as well as frequency domain methods. Entropy and other information theoretic notions are introduced, with applications to time series modeling
The book provides the foundation of time series methods, including linear filters and a geometric approach to prediction. The important paradigm of ARMA models is studied in-depth, as well as frequency domain methods. Entropy and other information theoretic notions are introduced, with applications to time series modeling
Tucker S. McElroy is Senior Time Series Mathematical Statistician at the U.S. Census Bureau, where he has contributed to developing time series research and software for the last 15 years. He has published more than 80 papers and is a recipient of the Arthur S. Flemming award (2011). Dimitris N. Politis is Distinguished Professor of Mathematics at the University of California at San Diego, where he is also serving as Associate Director of the Hal¿c¿ölu Data Science Institute. He has co-authored two research monographs and more than 100 journal papers. He is a recipient of the Tjalling C. Koopmans Econometric Theory Prize (2009-2011) and is Co-Editor of the Journal of Time Series Analysis.
Inhaltsangabe
1. Introduction 2. The Probabilistic Structure of Time Series 3. Trends Seasonality and Filtering 4. The Geometry of Random Variables 5. ARMA Models with White Noise Residuals 6. Time Series in the Frequency Domain 7. The Spectral Representation 8. Information and Entropy 9. Statistical Estimation 10. Fitting Time Series Models 11. Nonlinear Time Series Analysis 12. The Bootstrap A. Probability B. Mathematical Statistics C. Asymptotics D. Fourier Series E. Stieltjes Integration
1. Introduction 2. The Probabilistic Structure of Time Series 3. Trends Seasonality and Filtering 4. The Geometry of Random Variables 5. ARMA Models with White Noise Residuals 6. Time Series in the Frequency Domain 7. The Spectral Representation 8. Information and Entropy 9. Statistical Estimation 10. Fitting Time Series Models 11. Nonlinear Time Series Analysis 12. The Bootstrap A. Probability B. Mathematical Statistics C. Asymptotics D. Fourier Series E. Stieltjes Integration
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