Bayesian Dynamic Modelling

Bayesian time series and forecasting is a very broad field and any attempt at other than a very selective and personal overview of core and recent areas would be foolhardy. This chapter therefore selectively notes some key models and ideas, leavened with extracts from a few time series analysis and forecasting examples. For definitive development of core theory and methodology of Bayesian statespace models, readers are referred to [74,46] and might usefully read this chapter with one or both of the texts at hand for delving much further and deeper. The latter parts of the chapter link into and discuss a range of recent developments on specific modelling and applied topics in exciting and challenging areas of Bayesian time series analysis.