Author | dc.contributor.author | Casanova, María Paz | |
Author | dc.contributor.author | Orellana Zapata, Yasna | |
Admission date | dc.date.accessioned | 2017-10-24T17:49:46Z | |
Available date | dc.date.available | 2017-10-24T17:49:46Z | |
Publication date | dc.date.issued | 2016 | |
Cita de ítem | dc.identifier.citation | Communications in Statistics-Theory and Methods Volumen: 45 Número: 22 Páginas: 6596-6610 2016 | es_ES |
Identifier | dc.identifier.other | 10.1080/03610926.2014.963617 | |
Identifier | dc.identifier.uri | https://repositorio.uchile.cl/handle/2250/145338 | |
Abstract | dc.description.abstract | We 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 |
Lenguage | dc.language.iso | en | es_ES |
Publisher | dc.publisher | Taylor & Francis | es_ES |
Source | dc.source | Communications in Statistics-Theory and Methods | es_ES |
Keywords | dc.subject | Calibration problem | es_ES |
Keywords | dc.subject | MCMC | es_ES |
Keywords | dc.subject | Ordinal regression | es_ES |
Keywords | dc.subject | Skewed Dirichlet processes | es_ES |
Título | dc.title | A Bayesian semi-parametric approach to the ordinal calibration problem | es_ES |
Document type | dc.type | Artículo de revista | |
dcterms.accessRights | dcterms.accessRights | Acceso a solo metadatos | es_ES |
Cataloguer | uchile.catalogador | laj | es_ES |
Indexation | uchile.index | Artículo de publicación ISI | es_ES |