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dc.contributor.authorDelicado, Pedro
dc.contributor.authorGiraldo, Ramón
dc.contributor.authorComas Rodríguez, Carlos
dc.contributor.authorMateu, Jorge
dc.date.accessioned2012-11-09T20:20:12Z
dc.date.available2012-11-09T20:20:12Z
dc.date.issued2010
dc.identifier.citationEnvironmetrics Special Issue: Spatio-Temporal Stochastic Modelling: Environmental and Health Processes (2010) 21, 3-4, p. 224-239ca_CA
dc.identifier.issn1180-4009
dc.identifier.urihttp://hdl.handle.net/10234/51621
dc.description.abstractFunctional data analysis (FDA) is a relatively new branch in statistics. Experiments where a complete function is observed for each individual give rise to functional data. In this work we focus on the case of functional data presenting spatial dependence. The three classic types of spatial data structures (geostatistical data, point patterns, and areal data) can be combined with functional data as it is shown in the examples of each situation provided here. We also review some contributions in the literature on spatial functional data.ca_CA
dc.format.extent16 p.ca_CA
dc.language.isoengca_CA
dc.publisherJohn Wiley & Sons, Ltd.ca_CA
dc.rightsCopyright © 2009 John Wiley & Sons, Ltdca_CA
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/*
dc.subjectareal dataca_CA
dc.subjectfunctional data analysisca_CA
dc.subjectgeostatistical dataca_CA
dc.subjectpoint processesca_CA
dc.subjectsmoothingca_CA
dc.titleStatistics for spatial functional data: some recent contributionsca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttp://dx.doi.org/10.1002/env.1003
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccessca_CA
dc.relation.publisherVersionhttp://onlinelibrary.wiley.com/doi/10.1002/env.1003/abstractca_CA
dc.type.versioninfo:eu-repo/semantics/publishedVersion


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