Classification rules for multivariate repeated measures data with equicorrelated correlation structure on both time and spatial repeated measurements

Volver a la Vista simple
dc.conicet.fuenteindividual
dc.conicet.organizacionUniversity of Texas
dc.conicet.organizacionUniversidad Nacional de Cuyo
dc.conicet.organizacionConsejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza
dc.conicet.paisOrganizacionEstados Unidos
dc.conicet.paisOrganizacionArgentina
dc.conicet.paisOrganizacionArgentina
dc.conicet.produccionid3163393
dc.contributor.authorRoy, Anuradha
dc.contributor.authorLeiva, Ricardo Anibal
dc.date.accessioned2023-05-29T11:30:30Z
dc.date.available2023-05-29T11:30:30Z
dc.date.issued2012-12
dc.date.updated2023-05-24T14:25:13Z
dc.description.abstractWe study the problem of classification for multivariate repeated measures data with structured correlations on both time and spatial repeated measurements. This is a very important problem in many biomedical as well as in engineering field. Classification rules as well as the algorithm to compute the maximum likelihood estimates of the required parameters are given.es
dc.description.filFil: Roy, Anuradha. University of Texas; Estados Unidos
dc.description.filFil: Leiva, Ricardo Anibal. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina
dc.formatapplication/pdfes
dc.identifier.citationRoy, Anuradha; Leiva, Ricardo Anibal; Classification rules for multivariate repeated measures data with equicorrelated correlation structure on both time and spatial repeated measurements; Taylor & Francis; Communications In Statistics-theory And Methods; 41; 8; 12-2012; 1411-1420es
dc.identifier.institucionalCONICET
dc.identifier.issn0361-0926es
dc.identifier.repoCONICET Digital
dc.identifier.urihttp://hdl.handle.net/11336/198706
dc.journal.ciudadLondreses
dc.journal.number8es
dc.journal.pagination1411-1420es
dc.journal.paisReino Unidoes
dc.journal.titleCommunications In Statistics-theory And Methodses
dc.journal.volume41es
dc.language.isoenges
dc.publisherTaylor & Francises
dc.relation.alternativeidinfo:eu-repo/semantics/altIdentifier/url/https://www.tandfonline.com/doi/abs/10.1080/03610926.2010.530369
dc.relation.alternativeidinfo:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1080/03610926.2010.530369
dc.rightsinfo:eu-repo/semantics/openAccess*
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/*
dc.subjectCOVARIANCE STRUCTUREes
dc.subjectMAXIMUM LIKELIHOOD ESTIMATESes
dc.subjectREPEATED OBSERVATIONSes
dc.subject.classificationEstadística y Probabilidades
dc.subject.classificationMatemáticases
dc.subject.classificationCIENCIAS NATURALES Y EXACTASes
dc.titleClassification rules for multivariate repeated measures data with equicorrelated correlation structure on both time and spatial repeated measurementses
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:ar-repo/semantics/artículo
dc.typeinfo:eu-repo/semantics/publishedVersion

Archivos

Bloque original

Miniatura
Nombre:
CONICET_Digital_Nro.cc35221a-e677-424d-b9f8-6dd4385d9870_B.pdf
Tamaño:
136.33 KB
Formato:
Adobe Portable Document Format
Descargar

Colecciones

Articulos(CCT - MENDOZA)
Volver a la Vista simple