An overview of kriging and cokriging predictors for functional random fields

Detalhes bibliográficos
Autor(a) principal: Giraldo, Ramón
Data de Publicação: 2023
Outros Autores: Leiva, Víctor, Castro, Cecília
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/1822/86362
Resumo: This article presents an overview of methodologies for spatial prediction of functional data, focusing on both stationary and non-stationary conditions. A significant aspect of the functional random fields analysis is evaluating stationarity to characterize the stability of statistical properties across the spatial domain. The article explores methodologies from the literature, providing insights into the challenges and advancements in functional geostatistics. This work is relevant from theoreti cal and practical perspectives, offering an integrated view of methodologies tailored to the specific stationarity conditions of the functional processes under study. The practical implications of our work span across fields like environmental monitoring, geosciences, and biomedical research. This overview encourages advancements in functional geostatistics, paving the way for the development of innovative techniques for analyzing and predicting spatially correlated functional data. It lays the groundwork for future research, enhancing our understanding of spatial statistics and its applications.
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spelling An overview of kriging and cokriging predictors for functional random fieldsFunctional dataGeostatisticsKrigingNon-stationaritySpatial predictionStationarityCiências Naturais::MatemáticasEducação de qualidadeThis article presents an overview of methodologies for spatial prediction of functional data, focusing on both stationary and non-stationary conditions. A significant aspect of the functional random fields analysis is evaluating stationarity to characterize the stability of statistical properties across the spatial domain. The article explores methodologies from the literature, providing insights into the challenges and advancements in functional geostatistics. This work is relevant from theoreti cal and practical perspectives, offering an integrated view of methodologies tailored to the specific stationarity conditions of the functional processes under study. The practical implications of our work span across fields like environmental monitoring, geosciences, and biomedical research. This overview encourages advancements in functional geostatistics, paving the way for the development of innovative techniques for analyzing and predicting spatially correlated functional data. It lays the groundwork for future research, enhancing our understanding of spatial statistics and its applications.This research was partially supported by FONDECYT, grant number 1200525 (V.L.), from the National Agency for Research and Development (ANID) of the Chilean government under the Ministry of Science, Technology, Knowledge, and Innovation; and by Portuguese funds through the CMAT—Research Centre of Mathematics of University of Minho—within projects UIDB/00013/2020 and UIDP/00013/2020 (C.C.).Multidisciplinary Digital Publishing Institute (MDPI)Universidade do MinhoGiraldo, RamónLeiva, VíctorCastro, Cecília2023-08-072023-08-07T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/86362eng2227-739010.3390/math111534253425https://www.mdpi.com/2227-7390/11/15/3425info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-09-16T01:16:46Zoai:repositorium.sdum.uminho.pt:1822/86362Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:29:20.325021Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv An overview of kriging and cokriging predictors for functional random fields
title An overview of kriging and cokriging predictors for functional random fields
spellingShingle An overview of kriging and cokriging predictors for functional random fields
Giraldo, Ramón
Functional data
Geostatistics
Kriging
Non-stationarity
Spatial prediction
Stationarity
Ciências Naturais::Matemáticas
Educação de qualidade
title_short An overview of kriging and cokriging predictors for functional random fields
title_full An overview of kriging and cokriging predictors for functional random fields
title_fullStr An overview of kriging and cokriging predictors for functional random fields
title_full_unstemmed An overview of kriging and cokriging predictors for functional random fields
title_sort An overview of kriging and cokriging predictors for functional random fields
author Giraldo, Ramón
author_facet Giraldo, Ramón
Leiva, Víctor
Castro, Cecília
author_role author
author2 Leiva, Víctor
Castro, Cecília
author2_role author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Giraldo, Ramón
Leiva, Víctor
Castro, Cecília
dc.subject.por.fl_str_mv Functional data
Geostatistics
Kriging
Non-stationarity
Spatial prediction
Stationarity
Ciências Naturais::Matemáticas
Educação de qualidade
topic Functional data
Geostatistics
Kriging
Non-stationarity
Spatial prediction
Stationarity
Ciências Naturais::Matemáticas
Educação de qualidade
description This article presents an overview of methodologies for spatial prediction of functional data, focusing on both stationary and non-stationary conditions. A significant aspect of the functional random fields analysis is evaluating stationarity to characterize the stability of statistical properties across the spatial domain. The article explores methodologies from the literature, providing insights into the challenges and advancements in functional geostatistics. This work is relevant from theoreti cal and practical perspectives, offering an integrated view of methodologies tailored to the specific stationarity conditions of the functional processes under study. The practical implications of our work span across fields like environmental monitoring, geosciences, and biomedical research. This overview encourages advancements in functional geostatistics, paving the way for the development of innovative techniques for analyzing and predicting spatially correlated functional data. It lays the groundwork for future research, enhancing our understanding of spatial statistics and its applications.
publishDate 2023
dc.date.none.fl_str_mv 2023-08-07
2023-08-07T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/1822/86362
url https://hdl.handle.net/1822/86362
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2227-7390
10.3390/math11153425
3425
https://www.mdpi.com/2227-7390/11/15/3425
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute (MDPI)
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute (MDPI)
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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