Asymptotic properties of nonparametric estimation and quantile regression in Bayesian structural equation models
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Gwangsu | - |
dc.contributor.author | Choi, Taeryon | - |
dc.date.accessioned | 2021-09-01T15:41:03Z | - |
dc.date.available | 2021-09-01T15:41:03Z | - |
dc.date.created | 2021-06-19 | - |
dc.date.issued | 2019-05 | - |
dc.identifier.issn | 0047-259X | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/65834 | - |
dc.description.abstract | We study the asymptotic properties of nonparametric Bayesian structural equation models (SEMs). Under mild conditions, when adjusting nonparametric error distributions, the posteriors of Bayesian SEMs achieve the optimal convergence rate up to log n terms in the nonparametric means and nonlinear relationships of the latent variables. Furthermore, we consider quantile regressions of the error and latent variables in Bayesian SEMs, and we show posterior consistency in Bayesian quantile regression. The theoretical results are validated using simulation studies. (C) 2018 Elsevier Inc. All rights reserved. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER INC | - |
dc.subject | LATENT VARIABLE MODELS | - |
dc.subject | GIBBS SAMPLING METHODS | - |
dc.subject | POSTERIOR CONSISTENCY | - |
dc.title | Asymptotic properties of nonparametric estimation and quantile regression in Bayesian structural equation models | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Choi, Taeryon | - |
dc.identifier.doi | 10.1016/j.jmva.2018.11.009 | - |
dc.identifier.scopusid | 2-s2.0-85058169194 | - |
dc.identifier.wosid | 000463305300005 | - |
dc.identifier.bibliographicCitation | JOURNAL OF MULTIVARIATE ANALYSIS, v.171, pp.68 - 82 | - |
dc.relation.isPartOf | JOURNAL OF MULTIVARIATE ANALYSIS | - |
dc.citation.title | JOURNAL OF MULTIVARIATE ANALYSIS | - |
dc.citation.volume | 171 | - |
dc.citation.startPage | 68 | - |
dc.citation.endPage | 82 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.subject.keywordPlus | LATENT VARIABLE MODELS | - |
dc.subject.keywordPlus | GIBBS SAMPLING METHODS | - |
dc.subject.keywordPlus | POSTERIOR CONSISTENCY | - |
dc.subject.keywordAuthor | B-spline | - |
dc.subject.keywordAuthor | Convergence rate | - |
dc.subject.keywordAuthor | Latent variable | - |
dc.subject.keywordAuthor | Nonparametric statistics | - |
dc.subject.keywordAuthor | Structural equation model | - |
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