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Discussion on Competition for Spatial Statistics for Large Datasets

We discuss the experiences and results of the AppStatUZH team’s participation in the comprehensive and unbiased comparison of different spatial approximations conducted in the Competition for Spatial Statistics for Large Datasets. In each of the different sub-competitions, we estimated parameters of...

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Detalles Bibliográficos
Autores principales: Flury, Roman, Furrer, Reinhard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8541939/
https://www.ncbi.nlm.nih.gov/pubmed/34720575
http://dx.doi.org/10.1007/s13253-021-00461-3
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author Flury, Roman
Furrer, Reinhard
author_facet Flury, Roman
Furrer, Reinhard
author_sort Flury, Roman
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description We discuss the experiences and results of the AppStatUZH team’s participation in the comprehensive and unbiased comparison of different spatial approximations conducted in the Competition for Spatial Statistics for Large Datasets. In each of the different sub-competitions, we estimated parameters of the covariance model based on a likelihood function and predicted missing observations with simple kriging. We approximated the covariance model either with covariance tapering or a compactly supported Wendland covariance function.
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spelling pubmed-85419392021-10-27 Discussion on Competition for Spatial Statistics for Large Datasets Flury, Roman Furrer, Reinhard J Agric Biol Environ Stat Article We discuss the experiences and results of the AppStatUZH team’s participation in the comprehensive and unbiased comparison of different spatial approximations conducted in the Competition for Spatial Statistics for Large Datasets. In each of the different sub-competitions, we estimated parameters of the covariance model based on a likelihood function and predicted missing observations with simple kriging. We approximated the covariance model either with covariance tapering or a compactly supported Wendland covariance function. Springer US 2021-07-24 2021 /pmc/articles/PMC8541939/ /pubmed/34720575 http://dx.doi.org/10.1007/s13253-021-00461-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Flury, Roman
Furrer, Reinhard
Discussion on Competition for Spatial Statistics for Large Datasets
title Discussion on Competition for Spatial Statistics for Large Datasets
title_full Discussion on Competition for Spatial Statistics for Large Datasets
title_fullStr Discussion on Competition for Spatial Statistics for Large Datasets
title_full_unstemmed Discussion on Competition for Spatial Statistics for Large Datasets
title_short Discussion on Competition for Spatial Statistics for Large Datasets
title_sort discussion on competition for spatial statistics for large datasets
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8541939/
https://www.ncbi.nlm.nih.gov/pubmed/34720575
http://dx.doi.org/10.1007/s13253-021-00461-3
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