Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/11387
Título: | Geostatistical inference under preferential sampling |
Autor(es): | Diggle, Peter Menezes, Raquel Su Ting-li |
Palavras-chave: | Environmental monitoring Geostatistics Log-Gaussian Cox process Preferential sampling Marked point process Monte Carlo inference |
Data: | 2010 |
Editora: | Wiley |
Revista: | Journal of Royal Statistics Society, Series C |
Citação: | "Journal of Royal Statistics Society. Series C". ISSN 1467-9876. 59:2 (2010) 191-232. |
Resumo(s): | Geostatistics involves the fitting of spatially continuous models to spatially discrete data (Chil`es and Delfiner, 1999). 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 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 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 bio-monitoring data from Galicia, northern Spain, in which making allowance for preferential sampling materially changes the results of the analysis. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/11387 |
DOI: | 10.1111/j.1467-9876.2009.00701.x |
ISSN: | 1467-9876 |
Versão da editora: | http://www3.interscience.wiley.com/journal/117997424/home |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CMAT - Artigos em revistas com arbitragem / Papers in peer review journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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geopref_revised_final.pdf | Documento principal | 1,01 MB | Adobe PDF | Ver/Abrir |