A note on robust and non-robust variogram estimators

Detalhes bibliográficos
Autor(a) principal: Mingoti,Sueli Aparecida
Data de Publicação: 2008
Outros Autores: Rosa,Gilmar
Tipo de documento: Artigo
Idioma: eng
Título da fonte: REM. Revista Escola de Minas (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0370-44672008000100014
Resumo: In 1998 Genton proposed a variogram estimator claimed to be robust against outliers and compared it to Matheron's and Cressie-Hawkins' variogram estimators. Lark (2000) extended the comparison evaluating the effects of nonnormality. However, the comparison was limited to the spherical variogram model. In this paper 4 variogram estimators are compared including Genton's by using Monte Carlo simulation. Data with and without outliers were simulated using the spherical, exponential and wave models. The results showed that Genton's and the Median estimators were the best choices for contaminated data, while those of Matheron and Haslett presented better results for non-contaminated date; this latter being appropriate only for time series analysis.
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spelling A note on robust and non-robust variogram estimatorsSpatial statisticsrobust and non-robust variogram estimatorsoutliersIn 1998 Genton proposed a variogram estimator claimed to be robust against outliers and compared it to Matheron's and Cressie-Hawkins' variogram estimators. Lark (2000) extended the comparison evaluating the effects of nonnormality. However, the comparison was limited to the spherical variogram model. In this paper 4 variogram estimators are compared including Genton's by using Monte Carlo simulation. Data with and without outliers were simulated using the spherical, exponential and wave models. The results showed that Genton's and the Median estimators were the best choices for contaminated data, while those of Matheron and Haslett presented better results for non-contaminated date; this latter being appropriate only for time series analysis.Escola de Minas2008-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0370-44672008000100014Rem: Revista Escola de Minas v.61 n.1 2008reponame:REM. Revista Escola de Minas (Online)instname:Escola de Minasinstacron:ESCOLA DE MINAS10.1590/S0370-44672008000100014info:eu-repo/semantics/openAccessMingoti,Sueli AparecidaRosa,Gilmareng2008-04-30T00:00:00Zoai:scielo:S0370-44672008000100014Revistahttp://www.scielo.br/remhttps://old.scielo.br/oai/scielo-oai.phpeditor@rem.com.br1807-03530370-4467opendoar:2008-04-30T00:00REM. Revista Escola de Minas (Online) - Escola de Minasfalse
dc.title.none.fl_str_mv A note on robust and non-robust variogram estimators
title A note on robust and non-robust variogram estimators
spellingShingle A note on robust and non-robust variogram estimators
Mingoti,Sueli Aparecida
Spatial statistics
robust and non-robust variogram estimators
outliers
title_short A note on robust and non-robust variogram estimators
title_full A note on robust and non-robust variogram estimators
title_fullStr A note on robust and non-robust variogram estimators
title_full_unstemmed A note on robust and non-robust variogram estimators
title_sort A note on robust and non-robust variogram estimators
author Mingoti,Sueli Aparecida
author_facet Mingoti,Sueli Aparecida
Rosa,Gilmar
author_role author
author2 Rosa,Gilmar
author2_role author
dc.contributor.author.fl_str_mv Mingoti,Sueli Aparecida
Rosa,Gilmar
dc.subject.por.fl_str_mv Spatial statistics
robust and non-robust variogram estimators
outliers
topic Spatial statistics
robust and non-robust variogram estimators
outliers
description In 1998 Genton proposed a variogram estimator claimed to be robust against outliers and compared it to Matheron's and Cressie-Hawkins' variogram estimators. Lark (2000) extended the comparison evaluating the effects of nonnormality. However, the comparison was limited to the spherical variogram model. In this paper 4 variogram estimators are compared including Genton's by using Monte Carlo simulation. Data with and without outliers were simulated using the spherical, exponential and wave models. The results showed that Genton's and the Median estimators were the best choices for contaminated data, while those of Matheron and Haslett presented better results for non-contaminated date; this latter being appropriate only for time series analysis.
publishDate 2008
dc.date.none.fl_str_mv 2008-03-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0370-44672008000100014
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0370-44672008000100014
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0370-44672008000100014
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Escola de Minas
publisher.none.fl_str_mv Escola de Minas
dc.source.none.fl_str_mv Rem: Revista Escola de Minas v.61 n.1 2008
reponame:REM. Revista Escola de Minas (Online)
instname:Escola de Minas
instacron:ESCOLA DE MINAS
instname_str Escola de Minas
instacron_str ESCOLA DE MINAS
institution ESCOLA DE MINAS
reponame_str REM. Revista Escola de Minas (Online)
collection REM. Revista Escola de Minas (Online)
repository.name.fl_str_mv REM. Revista Escola de Minas (Online) - Escola de Minas
repository.mail.fl_str_mv editor@rem.com.br
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