Show simple item record

A Bayesian semi-parametric approach to the ordinal calibration problem

Authordc.contributor.authorCasanova, María Paz 
Authordc.contributor.authorOrellana Zapata, Yasna 
Admission datedc.date.accessioned2017-10-24T17:49:46Z
Available datedc.date.available2017-10-24T17:49:46Z
Publication datedc.date.issued2016
Cita de ítemdc.identifier.citationCommunications in Statistics-Theory and Methods Volumen: 45 Número: 22 Páginas: 6596-6610 2016es_ES
Identifierdc.identifier.other10.1080/03610926.2014.963617
Identifierdc.identifier.urihttp://repositorio.uchile.cl/handle/2250/145338
Abstractdc.description.abstractWe introduce a semi-parametric Bayesian approach based on skewed Dirichlet processes priors for location parameters in the ordinal calibration problem. This approach allows the modeling of asymmetrical error distributions. Conditional posterior distributions are implemented, thus allowing the use of Markov chains Monte Carlo to generate the posterior distributions. The methodology is applied to both simulated and real data.es_ES
Lenguagedc.language.isoenes_ES
Publisherdc.publisherTaylor & Francises_ES
Sourcedc.sourceCommunications in Statistics-Theory and Methodses_ES
Keywordsdc.subjectCalibration problemes_ES
Keywordsdc.subjectMCMCes_ES
Keywordsdc.subjectOrdinal regressiones_ES
Keywordsdc.subjectSkewed Dirichlet processeses_ES
Títulodc.titleA Bayesian semi-parametric approach to the ordinal calibration problemes_ES
Document typedc.typeArtículo de revistaes_ES
Catalogueruchile.catalogadorlajes_ES
Indexationuchile.indexArtículo de publicación ISIes_ES
Access notedct.AccessRightsSin acceso a texto completoes_ES


Files in this item

Icon

This item appears in the following Collection(s)

Show simple item record