variable selection in a partially linear proportional hazards model with a diverging dimensionality

variable selection in a partially linear proportional hazards model with a diverging dimensionality

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时间:2018-02-10

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1、StatisticsandProbabilityLetters83(2013)61–69ContentslistsavailableatSciVerseScienceDirectStatisticsandProbabilityLettersjournalhomepage:www.elsevier.com/locate/staproVariableselectioninapartiallylinearproportionalhazardsmodelwithadivergingdimensionalityY

2、uaoHu,HengLian∗DivisionofMathematicalSciences,SPMS,NanyangTechnologicalUniversitySingapore,637371,SingaporearticleinfoabstractArticlehistory:WeconsidertheproblemofsimultaneousvariableselectionandestimationinpartiallyReceived25May2012linearproportionalhaz

3、ardsmodelswhenthenumberofcovariatesinthelinearpartReceivedinrevisedform27August2012divergeswiththesamplesize.Weapplythesmoothlyclippedabsolutedeviation(SCAD)Accepted28August2012penaltytoselectthesignificantcovariatesinthelinearpart.Somesimulationsandarea

4、lAvailableonline5September2012datasetarepresented.©2012ElsevierB.V.Allrightsreserved.Keywords:Akaikeinformationcriterion(AIC)Bayesianinformationcriterion(BIC)Cross-validationPartiallikelihoodSCAD1.IntroductionNowadays,moreandmoreresearchersareconcernedwi

5、thdataanalysistasksinwhichalargenumberofpredic-tors/featuresareused.Thisisduetothefactthat,inastudywheretherearelimitedpreviousexperiences,itishardtoidentifyasmallnumberofpredictorssuchthatitisbelievedthatonlythesevariablescontributetotheresponseofintere

6、st.Thusalargenumberofpredictorssuspectedtoberelatedtoresponsesneedtobecollectedtoavoidmodelmisspecification.Ontheotherhand,duetothelargenumberofpredictorscollected,itisdesirabletoselectasmallnumberofpredictorsthatarerelevantforprediction.Variableselectio

7、nisanimportantresearchtopicinmodernstatistics.Withalargenumberofpredictorsavailabletoincludeintothemodel,manyofthemmaynotberelevantforprediction,andinclusionoftheseonlyhurtsestimationperformance.Recently,therehasbeenconsiderableinterestininvestigatingthe

8、variableselectionproblemforparametricandnonparametricmodels.Traditionalvariableselectionmethodssuchasstepwiseregressionandbestsubsetselectionsufferfrominstability,asarguedinBreiman(1996),whichispartofthereasonwhyapenalizat

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