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Discussion on "Competition on Spatial Statistics for Large Datasets".
Allard, Denis; Clarotto, Lucia; Opitz, Thomas; Romary, Thomas.
Afiliação
  • Allard D; Biostatistics and Spatial Processes (BioSP), INRAE, 84914 Avignon, France.
  • Clarotto L; MINES ParisTech, PSL University, Centre de Geosciences, 77300 Fontainebleau, France.
  • Opitz T; Biostatistics and Spatial Processes (BioSP), INRAE, 84914 Avignon, France.
  • Romary T; MINES ParisTech, PSL University, Centre de Geosciences, 77300 Fontainebleau, France.
J Agric Biol Environ Stat ; 26(4): 604-611, 2021.
Article em En | MEDLINE | ID: mdl-34335011
We discuss the methods and results of the RESSTE team in the competition on spatial statistics for large datasets. In the first sub-competition, we implemented block approaches both for the estimation of the covariance parameters and for prediction using ordinary kriging. In the second sub-competition, a two-stage procedure was adopted. In the first stage, the marginal distribution is estimated neglecting spatial dependence, either according to the flexible Tuckey g and h distribution or nonparametrically. In the second stage, estimation of the covariance parameters and prediction are performed using Kriging. Vecchias's approximation implemented in the GpGp package proved to be very efficient. We then make some propositions for future competitions. SUPPLEMENTARY INFORMATION: The online version supplementary material available at 10.1007/s13253-021-00462-2.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2021 Tipo de documento: Article