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Methods for preferential sampling in geostatistics

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  • Daniel Dinsdale
  • Matias Salibian‐Barrera

Abstract

Preferential sampling in geostatistics occurs when the locations at which observations are made may depend on the spatial process that underlines the correlation structure of the measurements. We show that previously proposed Monte Carlo estimates for the likelihood function may not be approximating the desired function. Furthermore, we argue that, for preferential sampling of moderate complexity, alternative and widely available numerical methods to approximate the likelihood function produce better results than Monte Carlo methods. We illustrate our findings on the Galicia data set analysed previously in the literature.

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  • Daniel Dinsdale & Matias Salibian‐Barrera, 2019. "Methods for preferential sampling in geostatistics," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 68(1), pages 181-198, January.
    • Handle: RePEc:bla:jorssc:v:68:y:2019:i:1:p:181-198
    DOI: 10.1111/rssc.12286
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    Cited by:

    1. Aubry, Philippe & Francesiaz, Charlotte & Guillemain, Matthieu, 2024. "On the impact of preferential sampling on ecological status and trend assessment," Ecological Modelling, Elsevier, vol. 492(C).

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