ABSTRACT
Having reviewed the basics of inference and computing under the hierarchical Bayesian modeling paradigm, we now turn our attention to its application in the setting of univariate point-referenced and areal unit data. Many of the models discussed in Chapter 3 and Chapter 4 will be of interest, but now they may be introduced in either the first-stage specification, to directly model the data in a spatial fashion, or in the second-stage specification, to model spatial structure in the random effects. We begin with models for point-level data, and proceed on to areal data models.
