Geostatistical analysis under preferential sampling (with discussion)

Diggle, P.J. and Menezes, R. and Su, T.L. (2010) Geostatistical analysis under preferential sampling (with discussion). Journal of the Royal Statistical Society Series C (Applied Statistics), 59 (2). pp. 191-232. ISSN 0035-9254

Full text not available from this repository.

Official URL: http://onlinelibrary.wiley.com/doi/10.1111/j.1467-...

Abstract

Geostatistics involves the fitting of spatially continuous models to spatially discrete data. Preferential sampling arises when the process that determines the data locations and the process being modelled are stochastically dependent. Conventional geostatistical methods assume, if only implicitly, that sampling is non-preferential. However, these methods are often used in situations where sampling is likely to be preferential. For example, in mineral exploration, samples may be concentrated in areas that are thought likely to yield high grade ore. We give a general expression for the likelihood function of preferentially sampled geostatistical data and describe how this can be evaluated approximately by using Monte Carlo methods. We present a model for preferential sampling and demonstrate through simulated examples that ignoring preferential sampling can lead to misleading inferences. We describe an application of the model to a set of biomonitoring data from Galicia, northern Spain, in which making allowance for preferential sampling materially changes the results of the analysis.

Item Type:Article
Subjects:5. Quantitative Data Handling and Data Analysis > 5.9 Spatial Data Analysis
ID Code:801
Deposited By: L-W-S user
Deposited On:19 May 2010 14:11
Last Modified:03 Feb 2012 14:35

Repository Staff Only: item control page