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Testing a hierarchical sequence of linear logistic models

dc.book.titleSoft Methodology and Random Information Systems
dc.contributor.authorPardo Llorente, Julio Ángel
dc.contributor.authorPardo Llorente, María del Carmen
dc.contributor.editorLópez-Díaz, Miguel C.
dc.contributor.editorGil, M. Angeles
dc.contributor.editorGrzegorzewski, Przemyslaw
dc.contributor.editorHryniewicz, Olgierd
dc.contributor.editorLawry, Jonathan
dc.date.accessioned2023-06-20T13:38:54Z
dc.date.available2023-06-20T13:38:54Z
dc.date.issued2004
dc.description2nd International Conference on Soft Methods in Probability and Statistics (SMPS 2004) SEP 02, 2004-SEP 04, 2007 Oviedo, SPAIN
dc.description.abstractThe inference problem we consider is that of model choice from a sequence of nested linear logistic models. The approach we take is to test successively, from most general to most specific, the corresponding sequence of composite hypotheses. This approach is based on the very general class of divergence measures, the phi-divergence.
dc.description.departmentDepto. de Estadística e Investigación Operativa
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.refereedTRUE
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/17989
dc.identifier.isbn978-3-540-22264-4
dc.identifier.officialurlhttp://www.springer.com/engineering/computational+intelligence+and+complexity/book/978-3-540-22264-4
dc.identifier.relatedurlhttp://www.springer.com
dc.identifier.urihttps://hdl.handle.net/20.500.14352/53194
dc.issue.number26
dc.page.final354
dc.page.initial347
dc.page.total760
dc.publication.placeBerlín
dc.publisherSpringer
dc.relation.ispartofseriesAdvances in Intelligent and Soft Computing
dc.rights.accessRightsmetadata only access
dc.subject.cdu519.233.5
dc.subject.keywordDivergence
dc.subject.ucmEstadística matemática (Matemáticas)
dc.subject.unesco1209 Estadística
dc.titleTesting a hierarchical sequence of linear logistic models
dc.typebook part
dspace.entity.typePublication
relation.isAuthorOfPublication5e051d08-2974-4236-9c25-5e14369a7b61
relation.isAuthorOfPublication.latestForDiscovery5e051d08-2974-4236-9c25-5e14369a7b61

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