Nonparametric Significance Testing And Group Variable Selection

dc.creatorZambom A.Z.
dc.creatorAkritas M.G.
dc.date2015
dc.date2015-06-25T12:54:13Z
dc.date2015-11-26T15:15:18Z
dc.date2015-06-25T12:54:13Z
dc.date2015-11-26T15:15:18Z
dc.date.accessioned2018-03-28T22:25:08Z
dc.date.available2018-03-28T22:25:08Z
dc.identifier
dc.identifierJournal Of Multivariate Analysis. Academic Press Inc., v. 133, n. , p. 51 - 60, 2015.
dc.identifier0047259X
dc.identifier10.1016/j.jmva.2014.08.014
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84907970195&partnerID=40&md5=7bbb1569371d1164557b05f3351b4f60
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/85567
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/85567
dc.identifier2-s2.0-84907970195
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1258987
dc.descriptionIn the context of a heteroscedastic nonparametric regression model, we develop a test for the null hypothesis that a subset of the predictors has no influence on the regression function. The test uses residuals obtained from local polynomial fitting of the null model and is based on a test statistic inspired from high-dimensional analysis of variance. Using p-values from this test, and multiple testing ideas, a group variable selection method is proposed, which can consistently select even groups of variables with diminishing predictive significance. A backward elimination version of this procedure, called GBEAMS for Group Backward Elimination Anova-type Model Selection, is recommended for practical applications. Simulation studies, suggest that the proposed test procedure outperforms the generalized likelihood ratio test when the alternative is non-additive or there is heteroscedasticity. Additional simulation studies reveal that the proposed group variable selection procedure performs competitively against other variable selection methods, and outperforms them in selecting groups having nonlinear or dependent effects. The proposed group variable selection procedure is illustrated on a real data set.
dc.description133
dc.description
dc.description51
dc.description60
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dc.languageen
dc.publisherAcademic Press Inc.
dc.relationJournal of Multivariate Analysis
dc.rightsfechado
dc.sourceScopus
dc.titleNonparametric Significance Testing And Group Variable Selection
dc.typeArtículos de revistas


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