Hierarchical Modeling and Analysis for Spatial Data

Substantially updated, this self-contained second edition uses Bayesian hierarchical models in the analysis of spatial data. Three new chapters cover hierarchical models for point-process data with a focus on Bayesian inference in the presence of spatial and non-spatial predictors; the modeling of large spatial and spatial-temporal data sets; and spatial gradients. This edition also addresses other new topics, such as spatial survival models, dynamic spatial frailty models, and multi-scale and nested spatial models. Computer tutorials on R and WinBUGS are also included.