Design of Experiments and Sample Surveys Commons^™

Bayesian Geostatistical Design, Peter J. Diggle, Soren Lophaven

Johns Hopkins University, Dept. of Biostatistics Working Papers

This paper describes the use of model-based geostatistics for choosing the optimal set of sampling locations, collectively called the design, for a geostatistical analysis. Two types of design situations are considered. These are retrospective design, which concerns the addition of sampling locations to, or deletion of locations from, an existing design, and prospective design, which consists of choosing optimal positions for a new set of sampling locations. We propose a Bayesian design criterion which focuses on the goal of efficient spatial prediction whilst allowing for the fact that model parameter values are unknown. The results show that in this situation …