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dc.contributor.authorNasirzadeh, Roya
dc.contributor.authorMateu, Jorge
dc.contributor.authorSoltani, Ahmad Reza
dc.date.accessioned2019-12-11T11:42:15Z
dc.date.available2019-12-11T11:42:15Z
dc.date.issued2019-08-29
dc.identifier.citationNASIRZADEH, Roya; MATEU, Jorge; SOLTANI, Ahmad Reza. On a linear functional mixed effect model for spatial data. Journal of Iranian Statistical Society (JIRSS), 2019, 18.2: 115-137.ca_CA
dc.identifier.urihttp://hdl.handle.net/10234/185374
dc.description.abstractThis paper introduces a functional mixed effect random model to model spatial data. In this model, the spatial locations form the index set, while the contributing effects to the response variable are set as a linear mixture of fixed and random effects. These fixed and random effects are linear combinations of L2 functions and random elements, respectively. However, the corresponding linear factors depend on the spatial location variable. Therefore, we develop estimation procedures to estimate the fixed and random coefficients, using spatial functional principal component analysis. Then, we perform prediction by adapting the functional universal kriging method to our model.ca_CA
dc.format.extent24 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherIranian Statistical Societyca_CA
dc.rightsAtribución-NoComercial 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectfunctional principal componentsca_CA
dc.subjectKarhunen-Loeve expansionsca_CA
dc.subjectspatial functional mixed effect modelsca_CA
dc.subjectspatial functional random variableca_CA
dc.subjectuniversal krigingca_CA
dc.titleOn a Linear Functional Mixed Effect Model for Spatial Dataca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttps://doi.org/10.29252/jirss.18.2.115
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttp://jirss.irstat.ir/article-1-490-en.htmlca_CA
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_CA


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