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Department of Mathematical Sciences

Seminar Archives

On this page you can find information about seminars in this and previous academic years, where available on the database.

Statistics Seminars: Model-based geostatistics, preferential sampling and environmental monitoring

Presented by Peter Diggle, Department of Medicine, Lancaster University and Department of Biostatistics, Johns Hopkins University

5 February 2008 14:15 in CM221

Geostatistics is the branch of spatial statistics whose purpose is to make inferences about a spatially continuous phenomenon using spatially discrete data. Classical geostatistical methods were developed, principally at Ecole des Mines, Fontainebleau, independently of mainstream spatial statistics. The term model-based geostatistics was coined by Diggle, Moyeed and Tawn (1998) to refer to geostatistical analysis based on general statistical principles applied to an explicitly declared stochastic model; see also Diggle and Ribeiro (2007).

Preferential sampling refers to situations in which measurements of a spatial phenomenon are made at locations chosen by a mechanism that is stochastically dependent on the underlying phenomenon itself.

Preferential sampling appears to be widespread in practice, although it is often ignored. Environmental monitoring is a case in point, monitors often being placed near suspected pollution sources.

In this talk I will first review model-based geostatistical methods in the context of an application to tropical disease risk mapping (Diggle et al, 2007). I will then discuss how preferential sampling invalidates standard geostatistical methods and suggest possible remedies. Finally, I will describe an application to environmental monitoring data concerning heavy metal bio-monitoring in Galicia, Spain (Diggle, Menezes and Su, 2007).

Diggle, P.J. Moyeed, R.A. and Tawn, J.A. (1998). Model-based geostatistics (with Discussion). Applied Statistics, 47, 299-350.

Diggle, P.J. and Ribeiro, P.J. (2007). Model-based Geostatistics. New York: Springer.

Diggle, P.J., Thomson, M.C., Christensen, O.F., Rowlingson, B., Obsomer, V., Gardon, J., Wanji, S., Takougang, I., Enyong, P.,Kamgno, J., Remme, H., Boussinesq, M. and Molyneux, D.H. (2007). Spatial modelling and prediction of Loa loa risk: decision making under uncertainty. Annals of Tropical Medicine and Parasitology, 101, 499-509.

Diggle, P.J., Menezes, R. and Su, T-L. (2008). Geostatistical analysis under preferential sampling. (submitted)

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