ABSTRACT
This chapter has three key objectives. The first objective is to provide the reader with an introduction to Bayesian inference from a theoretical perspective (what do we mean by “Bayesian inference”), from a model building perspective (how do we construct a Bayesian model to tackle the problem in hand) and from a computational perspective (how do we implement/fit a Bayesian model using WinBUGS). The second objective is to discuss Bayesian regression modelling, laying the foundation for the more complex spatial and spatial-temporal modelling that will be discussed in Parts II and III of the book. Finally, to help fix ideas, the third objective is to provide some illustrative examples using spatial data of the type that we introduced in the examples in Chapter 1.
