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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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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 |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-8541939 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT fluryroman discussiononcompetitionforspatialstatisticsforlargedatasets AT furrerreinhard discussiononcompetitionforspatialstatisticsforlargedatasets |