Assessing the order of dependence for partially exchangeable binary data

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dc.contributor.authorQuintana, FA
dc.contributor.authorNewton, MA
dc.date.accessioned2024-01-10T12:04:21Z
dc.date.available2024-01-10T12:04:21Z
dc.date.issued1998
dc.description.abstractThe problem we consider is how to assess the order of serial dependence within partially exchangeable binary sequences, We obtain exact conditional tests comparing any two orders by finding the conditional distribution of data given certain transition counts. These tests are facilitated with a new Monte Carlo scheme. Asymptotic tests are also discussed. In particular, we show that the likelihood ratio tests have an asymptotic chi-squared distribution, thus generalizing the results of Billingsley for the particular case of Markov chains. We apply these methods to several datasets, and perform a simulation to study their properties.
dc.fechaingreso.objetodigital2024-05-17
dc.format.extent9 páginas
dc.fuente.origenWOS
dc.identifier.doi10.2307/2669616
dc.identifier.issn0162-1459
dc.identifier.urihttps://doi.org/10.2307/2669616
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/75770
dc.identifier.wosidWOS:000072355300020
dc.information.autorucMatemática;Quintana F;S/I;100343
dc.issue.numero441
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final202
dc.pagina.inicio194
dc.publisherAMER STATISTICAL ASSOC
dc.revistaJOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
dc.rightsacceso restringido
dc.subjectconditional simulation
dc.subjectMarkov chains
dc.subjectmodel selection
dc.subjectmultiple binary sequences
dc.subjectnonparametric mixtures
dc.subjectMARKOV-CHAIN MODELS
dc.subjectLOGISTIC-REGRESSION
dc.subjectMIXING DISTRIBUTION
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleAssessing the order of dependence for partially exchangeable binary data
dc.typeartículo
dc.volumen93
sipa.codpersvinculados100343
sipa.indexWOS
sipa.indexScopus
sipa.trazabilidadCarga SIPA;09-01-2024
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