Show simple item record

dc.contributor.authorCarpentier, Alexandra*
dc.contributor.authorCollier, Olivier*
dc.contributor.authorComminges, Laëtitia*
dc.contributor.authorTsybakov, Alexandre*
dc.contributor.authorWang, Yuhao*
dc.date.accessioned2018-09-04T10:01:13Z
dc.date.available2018-09-04T10:01:13Z
dc.date.issued2018
dc.identifier.issn0005-1179
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/17937
dc.language.isoenen
dc.subjectsignal detection
dc.subjectsparsity
dc.subjectGaussian sequence model
dc.subjectlinear regression
dc.subject.ddc519en
dc.titleMinimax rate of testing in sparse linear regression
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenWe consider the problem of testing the hypothesis that the parameter of linear regression model is 0 against an s-sparse alternative separated from 0 in the 2-distance. We show that, in Gaussian linear regression model with p < n, where p is the dimension of the parameter and n is the sample size, the non-asymptotic minimax rate of testing has the form sqrt((s/n) log(1 + sqrt(p)/s)). We also show that this is the minimax rate of estimation of the 2-norm of the regression parameter. MSC 2010 subject classifications: 62J05, 62G10.
dc.publisher.cityParis
dc.relation.isversionofjnlnameAutomation and Remote Control
dc.relation.isversionofjnlvol80
dc.relation.isversionofjnldate2018
dc.relation.isversionofjnlpages1817–1834
dc.relation.isversionofdoi10.1134/S0005117919100047
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.description.ssrncandidatenon
dc.description.halcandidatenon
dc.description.readershiprecherche
dc.description.audienceInternational
dc.relation.Isversionofjnlpeerreviewednon
dc.date.updated2020-07-01T12:18:31Z
hal.person.labIds120520*
hal.person.labIds101*
hal.person.labIds60*
hal.person.labIds2579$$$102*
hal.person.labIds543049*


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record