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.First, those state components were discussed that can be used to obtain an adequate description of the time series at hand: the level, the slope and the seasonal. For the log ... The log of the petrol price and the introduction of the seat belt law in February 1983 in the UK ... This could be explained by the fact that higher petrol prices result in a reduction of the number of vehicles circulating in 12Conclusions.
|Title||:||An Introduction to State Space Time Series Analysis|
|Author||:||Jacques J.F. Commandeur, Siem Jan Koopman|
|Publisher||:||OUP Oxford - 2007-07-19|