Time Series Analysis by State Space Methods (019964117X)

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This new edition updates Durbin & Koopman's important text on 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 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. Additions to this second edition include the filtering of nonlinear and non-Gaussian series.

Part I of the book obtains the mean and variance of the state, of a variable intended to measure the effect of an interaction and of regression coefficients, in terms of the observations.

Part II extends the treatment to nonlinear and non-normal models. For these, analytical solutions are not available so methods are based on simulation.

Product details

• Format Hardback | 368 pages
• Dimensions 161 x 235 x 26mm | 680g
• Publication date 01 Aug 2012
• Publisher Oxford University Press
• Publication City/Country Oxford, United Kingdom
• Language English
• Edition Revised
• Edition Statement 2nd Revised edition
• Illustrations note 34 b/w illustrations
• ISBN10 019964117X
• ISBN13 9780199641178
• Bestsellers rank 459,685

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