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Full Description
Providing a practical introduction to state space methods as applied to unobserved components time series models, also known as structural time series models, this book introduces time series analysis using state space methodology to readers who are neither familiar with time series analysis, nor with state space methods. The only background required in order to understand the material presented in the book is a basic knowledge of classical linear regression models, of which a brief review is provided to refresh the reader's knowledge. Also, a few sections assume familiarity with matrix algebra, however, these sections may be skipped without losing the flow of the exposition.
The book offers a step by step approach to the analysis of the salient features in time series such as the trend, seasonal, and irregular components. Practical problems such as forecasting and missing values are treated in some detail. This useful book will appeal to practitioners and researchers who use time series on a daily basis in areas such as the social sciences, quantitative history, biology and medicine. It also serves as an accompanying textbook for a basic time series course in econometrics and statistics, typically at an advanced undergraduate level or graduate level.
Contents
1. Introduction ; 2. The Local Level Model ; 3. The Local Linear Trend Model ; 4. The Local Level Model with Seasonal ; 5. The Local Level Model with Explanatory Variable ; 6. The Local Level Model with Intervention Variable ; 7. The UK Seat Belt and Inflation Models ; 8. General Treatment of Univariate State Space Models ; 9. Multivariate Time Series Analysis ; 10. State Space and Box-Jenkins Methods for Time Series Analysis ; 11. State Space Modelling in Practice ; 12. Conclusions ; Appendix A UK Drivers KSI and Petrol Price ; Appendix B Road Traffic Fatalities in Norway and Finland ; Appendix C UK Front and Rear Seat Passengers KSI ; Appendix D UK Price Changes
