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Bayesian Forecasting and Dynamic Models (Paperback, 2nd ed. 1997. Softcover reprint of the original 2nd ed. 1997)
Loot Price: R2,966
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Bayesian Forecasting and Dynamic Models (Paperback, 2nd ed. 1997. Softcover reprint of the original 2nd ed. 1997)
Series: Springer Series in Statistics
Expected to ship within 18 - 22 working days
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This text is concerned with Bayesian learning, inference and
forecasting in dynamic environments. We describe the structure and
theory of classes of dynamic models and their uses in forecasting
and time series analysis. The principles, models and methods of
Bayesian forecasting and time - ries analysis have been developed
extensively during the last thirty years.
Thisdevelopmenthasinvolvedthoroughinvestigationofmathematicaland
statistical aspects of forecasting models and related techniques.
With this has come experience with applications in a variety of
areas in commercial, industrial, scienti?c, and socio-economic
?elds. Much of the technical - velopment has been driven by the
needs of forecasting practitioners and applied researchers. As a
result, there now exists a relatively complete statistical and
mathematical framework, presented and illustrated here. In writing
and revising this book, our primary goals have been to present a
reasonably comprehensive view of Bayesian ideas and methods in m-
elling and forecasting, particularly to provide a solid reference
source for advanced university students and research workers.
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