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Time Series Analysis by State Space Methods
J. Durbin and S. J. Koopman

Description
Providing analyses from both classical and Bayesian perspectives, this book presents a comprehensive treatment of the state space approach to time series analysis. The distinguishing feature of state space time models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbance terms, each of which is modelled separately. The techniques that emerge from this approach are very flexible and are capable of handling a much wider range of problems than the main analytical system currently in use for time series analysis, the Box-Jenkins ARIMA system.

Reviews
"Providing analyses from both classical and Bayesian perspectives, this book presents a comprehensive treatment of the state space approach to time series analysis."--The Bulletin of Mathematics Books

Product Details272 pages; 28 line illus; ISBN13: 978-0-19-852354-3ISBN10: 0-19-852354-8
About the Author(s)
J. Durbin, Department of Statistics, London School of Economics and Political Science, and
S. J. Koopman, Department of Econometrics, Free University, Amersterdam