DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Cheolwoo | ko |
dc.contributor.author | Yoon, Young Joo | ko |
dc.date.accessioned | 2021-06-11T01:30:37Z | - |
dc.date.available | 2021-06-11T01:30:37Z | - |
dc.date.created | 2021-06-11 | - |
dc.date.created | 2021-06-11 | - |
dc.date.issued | 2011-11 | - |
dc.identifier.citation | JOURNAL OF STATISTICAL PLANNING AND INFERENCE, v.141, no.11, pp.3506 - 3519 | - |
dc.identifier.issn | 0378-3758 | - |
dc.identifier.uri | http://hdl.handle.net/10203/285759 | - |
dc.description.abstract | In high-dimensional regression problems regularization methods have been a popular choice to address variable selection and multicollinearity. In this paper we study bridge regression that adaptively selects the penalty order from data and produces flexible solutions in various settings. We implement bridge regression based on the local linear and quadratic approximations to circumvent the nonconvex optimization problem. Our numerical study shows that the proposed bridge estimators are a robust choice in various circumstances compared to other penalized regression methods such as the ridge, lasso, and elastic net. In addition, we propose group bridge estimators that select grouped variables and study their asymptotic properties when the number of covariates increases along with the sample size. These estimators are also applied to varying-coefficient models. Numerical examples show superior performances of the proposed group bridge estimators in comparisons with other existing methods. (C) 2011 Elsevier B.V. All rights reserved. | - |
dc.language | English | - |
dc.publisher | ELSEVIER SCIENCE BV | - |
dc.title | Bridge regression: Adaptivity and group selection | - |
dc.type | Article | - |
dc.identifier.wosid | 000293433400013 | - |
dc.identifier.scopusid | 2-s2.0-80955178309 | - |
dc.type.rims | ART | - |
dc.citation.volume | 141 | - |
dc.citation.issue | 11 | - |
dc.citation.beginningpage | 3506 | - |
dc.citation.endingpage | 3519 | - |
dc.citation.publicationname | JOURNAL OF STATISTICAL PLANNING AND INFERENCE | - |
dc.identifier.doi | 10.1016/j.jspi.2011.05.004 | - |
dc.contributor.localauthor | Park, Cheolwoo | - |
dc.contributor.nonIdAuthor | Yoon, Young Joo | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Analysis of variance | - |
dc.subject.keywordAuthor | Bridge regression | - |
dc.subject.keywordAuthor | Multicollinearity | - |
dc.subject.keywordAuthor | Oracle property | - |
dc.subject.keywordAuthor | Penalized regression | - |
dc.subject.keywordAuthor | Variable selection | - |
dc.subject.keywordAuthor | Varying-coefficient models | - |
dc.subject.keywordPlus | VARYING-COEFFICIENT MODELS | - |
dc.subject.keywordPlus | NONCONCAVE PENALIZED LIKELIHOOD | - |
dc.subject.keywordPlus | VARIABLE SELECTION | - |
dc.subject.keywordPlus | GROUP LASSO | - |
dc.subject.keywordPlus | ASYMPTOTIC PROPERTIES | - |
dc.subject.keywordPlus | ORACLE PROPERTIES | - |
dc.subject.keywordPlus | ELASTIC-NET | - |
dc.subject.keywordPlus | ESTIMATORS | - |
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