Titlebook: Bayesian Forecasting and Dynamic Models; Mike West,Jeff Harrison Book 19891st edition Springer Science+Business Media New York 1989 data a

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Illustrations and Extensions of Standard DLMS,l components are a useful first attack. If retrospective analysis is the primary goal, then these simple and purely descriptive models may be adequate in themselves, providing estimates of the trend (or deseasonalised series), seasonal pattern (detrended series) and irregular or random component ove

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Multivariate Modelling and Forecasting,al distribution, the univariate theory extends easily only when it is assumed that the observational error variance matrices are known for all time. However, as soon as uncertainties about observational variance matrices are admitted, the tractability of analysis is lost. In general, there is no nea

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Johanna Sefyrin,Mariana S. Gustafssonn-normal problems, the largest class being that based on the use of . for observational distributions. This Chapter is devoted to these models, the primary references being Migon (1984), Migon and Harrison (1985), and West and Harrison (1986a), West, Harrison and Migon (1985).

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