Time Series Analysis by State Space Methods

James Durbin and Siem Jan Koopman

in OUP Catalogue from Oxford University Press

Abstract: 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.

Date: 2001
ISBN: 9780198523543
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Book: Time Series Analysis by State Space Methods (2012)
Software Item: SEASONALDLM: RATS procedure to create the matrices for the seasonal component of a DLM
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