Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/5809

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dc.contributor.authorMenezes, Raquel-
dc.contributor.authorGarcía Soidán, Pilar-
dc.contributor.authorFebrero-Bande, Manuel-
dc.date.accessioned2006-11-22T13:58:05Z-
dc.date.available2006-11-22T13:58:05Z-
dc.date.issued2005-
dc.identifier.citation"Computational statistics". ISSN 0943-4062. 20:4 (2005) 623-642.eng
dc.identifier.issn0943-4062eng
dc.identifier.urihttp://hdl.handle.net/1822/5809-
dc.description.abstractVariogram estimation is a major issue for statistical inference of spatially correlated random variables. Most natural empirical estimators of the variogram cannot be used for this purpose, as they do not achieve the conditional negative-definite property. Typically, this problem's resolution is split into three stages: empirical variogram estimation; valid model selection; and model fitting. To accomplish these tasks, there are several different approaches strongly defended by their authors. Our work's main purpose was to identify these approaches and compare them based on a numerical study, covering different kind of spatial dependence situations. The comparisons are based on the integrated squared errors of the resulting valid estimators. Additionally, we propose an easily implementable empirical method to compare the main features of the estimated variogram function.eng
dc.language.isoengeng
dc.publisherSpringer eng
dc.rightsopenAccesseng
dc.subjectSpatial dependenceeng
dc.subjectEmpirical variogrameng
dc.subjectValid modeleng
dc.subjectFitting criteriaeng
dc.subjectNon-parametric estimationeng
dc.titleA comparison of approaches for valid variogram achievementeng
dc.typearticlepor
dc.peerreviewedyeseng
dc.relation.publisherversionhttp://comst.wiwi.hu-berlin.de/20_4.htmeng
sdum.number4eng
sdum.pagination623-642eng
sdum.publicationstatuspublishedeng
sdum.volume20eng
degois.publication.firstPage623por
degois.publication.lastPage642por
degois.publication.issue4por
degois.publication.volume20por
dc.identifier.doi10.1007/BF02741319por
dc.subject.wosScience & Technologypor
sdum.journalComputational statisticspor
Appears in Collections:Offmath - Artigos (Papers)

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