Time Series Analysis by State Space Methods: No.24 (Oxford Statistical Science Series) 1st edition hardback in very good condition

This excellent text provides a comprehensive treatment of the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbence 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. The book provides an excellent source for the development of practical courses on time series analysis.

James Durbin is at London School of Economics and Political Science. Siem Jan Koopman is at Department of Econometrics, Free University, Amsterdam, The Netherlands.