A note on Bayes factor consistency in partial linear models
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Choi, Taeryon | - |
dc.contributor.author | Rousseau, Judith | - |
dc.date.accessioned | 2021-09-04T10:59:41Z | - |
dc.date.available | 2021-09-04T10:59:41Z | - |
dc.date.created | 2021-06-10 | - |
dc.date.issued | 2015-11 | - |
dc.identifier.issn | 0378-3758 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/92022 | - |
dc.description.abstract | It has become increasingly important to understand the asymptotic behavior of the Bayes factor for model selection in general statistical models. In this paper, we discuss recent results on Bayes factor consistency in semiparametric regression problems where observations are independent but not identically distributed. Specifically, we deal with the model selection problem in the context of partial linear models in which the regression function is assumed to be the additive form of the parametric component and the nonparametric component using Gaussian process priors, and Bayes factor consistency is investigated for choosing between the parametric model and the semiparametric alternative. (C) 2015 Elsevier B.V. All rights reserved. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCIENCE BV | - |
dc.subject | GAUSSIAN PROCESS PRIORS | - |
dc.subject | POSTERIOR DISTRIBUTIONS | - |
dc.subject | NONPARAMETRIC ALTERNATIVES | - |
dc.subject | CONVERGENCE-RATES | - |
dc.subject | MIXTURES | - |
dc.subject | INFERENCE | - |
dc.subject | DENSITY | - |
dc.title | A note on Bayes factor consistency in partial linear models | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Choi, Taeryon | - |
dc.identifier.doi | 10.1016/j.jspi.2015.03.009 | - |
dc.identifier.scopusid | 2-s2.0-84940770948 | - |
dc.identifier.wosid | 000361257500014 | - |
dc.identifier.bibliographicCitation | JOURNAL OF STATISTICAL PLANNING AND INFERENCE, v.166, pp.158 - 170 | - |
dc.relation.isPartOf | JOURNAL OF STATISTICAL PLANNING AND INFERENCE | - |
dc.citation.title | JOURNAL OF STATISTICAL PLANNING AND INFERENCE | - |
dc.citation.volume | 166 | - |
dc.citation.startPage | 158 | - |
dc.citation.endPage | 170 | - |
dc.type.rims | ART | - |
dc.type.docType | Article; Proceedings Paper | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.subject.keywordPlus | GAUSSIAN PROCESS PRIORS | - |
dc.subject.keywordPlus | POSTERIOR DISTRIBUTIONS | - |
dc.subject.keywordPlus | NONPARAMETRIC ALTERNATIVES | - |
dc.subject.keywordPlus | CONVERGENCE-RATES | - |
dc.subject.keywordPlus | MIXTURES | - |
dc.subject.keywordPlus | INFERENCE | - |
dc.subject.keywordPlus | DENSITY | - |
dc.subject.keywordAuthor | Bayes factor | - |
dc.subject.keywordAuthor | Consistency | - |
dc.subject.keywordAuthor | Fourier series | - |
dc.subject.keywordAuthor | Gaussian processes | - |
dc.subject.keywordAuthor | Hellinger distance | - |
dc.subject.keywordAuthor | Kullback-Leibler neighborhoods | - |
dc.subject.keywordAuthor | Lack of fit testing | - |
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