Bayesian Geostatistical Design

Peter Diggle and Søren Lophaven

Scandinavian Journal of Statistics, 2006, vol. 33, issue 1, 53-64

Abstract: Abstract. This paper describes the use of model‐based geostatistics for choosing the set of sampling locations, collectively called the design, to be used in a geostatistical analysis. Two types of design situation 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 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 a wide range of inter‐point distances should be included in the design, and the widely used regular design is often not the best choice.

Date: 2006
References: View complete reference list from CitEc
Citations: View citations in EconPapers (18)

Downloads: (external link)
https://doi.org/10.1111/j.1467-9469.2005.00469.x

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:scjsta:v:33:y:2006:i:1:p:53-64

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0303-6898

Access Statistics for this article

Scandinavian Journal of Statistics is currently edited by ÿrnulf Borgan and Bo Lindqvist

More articles in Scandinavian Journal of Statistics from Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association, Swedish Statistical Association
Bibliographic data for series maintained by Wiley Content Delivery ().