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Article: A Bootstrap Recipe for Post-Model-Selection Inference under Linear Regression Models

TitleA Bootstrap Recipe for Post-Model-Selection Inference under Linear Regression Models
Authors
KeywordsBootstrap
Least squares estimator
Post-model-selection
Regression.
Issue Date2018
PublisherOxford University Press. The Journal's web site is located at http://biomet.oxfordjournals.org/
Citation
Biometrika, 2018, v. 105 n. 4, p. 873-890 How to Cite?
Persistent Identifierhttp://hdl.handle.net/10722/260593
ISSN
2019 Impact Factor: 1.632
2015 SCImago Journal Rankings: 2.801
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLee, SMS-
dc.contributor.authorWu, Y-
dc.date.accessioned2018-09-14T08:44:12Z-
dc.date.available2018-09-14T08:44:12Z-
dc.date.issued2018-
dc.identifier.citationBiometrika, 2018, v. 105 n. 4, p. 873-890-
dc.identifier.issn0006-3444-
dc.identifier.urihttp://hdl.handle.net/10722/260593-
dc.languageeng-
dc.publisherOxford University Press. The Journal's web site is located at http://biomet.oxfordjournals.org/-
dc.relation.ispartofBiometrika-
dc.rightsPre-print: Journal Title] ©: [year] [owner as specified on the article] Published by Oxford University Press [on behalf of xxxxxx]. All rights reserved. Pre-print (Once an article is published, preprint notice should be amended to): This is an electronic version of an article published in [include the complete citation information for the final version of the Article as published in the print edition of the Journal.] Post-print: This is a pre-copy-editing, author-produced PDF of an article accepted for publication in [insert journal title] following peer review. The definitive publisher-authenticated version [insert complete citation information here] is available online at: xxxxxxx [insert URL that the author will receive upon publication here].-
dc.subjectBootstrap-
dc.subjectLeast squares estimator-
dc.subjectPost-model-selection-
dc.subjectRegression.-
dc.titleA Bootstrap Recipe for Post-Model-Selection Inference under Linear Regression Models-
dc.typeArticle-
dc.identifier.emailLee, SMS: smslee@hku.hk-
dc.identifier.authorityLee, SMS=rp00726-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1093/biomet/asy046-
dc.identifier.scopuseid_2-s2.0-85058879051-
dc.identifier.hkuros291524-
dc.identifier.volume105-
dc.identifier.issue4-
dc.identifier.spage873-
dc.identifier.epage890-
dc.identifier.isiWOS:000452741300009-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl0006-3444-

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