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简介：Thispaperdealswithestimationandtestproceduresforrestrictedlinearerrors-invariables(EV)modelswithnonignorablemissingcovariates.Wedeveloparestrictedweightedcorrectedleastsquares(WCLS)estimatorbasedonthepropensityscore,whichisfittedbyanexponentiallytiltedlikelihoodmethod.Thelimitingdistributionsoftheproposedestimatorsarediscussedwhentiltedparameterisknownorunknown.Totestthevalidityoftheconstraints,weconstructtwotestproceduresbasedoncorrectedresidualsumofsquaresandempiricallikelihoodmethodandderivetheirasymptoticproperties.Numericalstudiesareconductedtoexaminethefinitesampleperformanceofourproposedmethods.

简介：Hypothesistestingfortheparametriccomponentinthepartiallinearerrors-in-variables(EV)regressionmodelsisdiscussedinthispaper.Basedonthecorrectedprofileleastsquareestimator,fiveteststatisticsareproposedandtheasymptoticnulldistributionsofthemarededuced.Simulationshavebeendonetoshowtheperformanceoftheseteststatisticsundernullandalternativehypothesis.

简介：Thispaperstudiesestimationandserialcorrelationtestofasemiparametricvarying-coefficientpartiallylinearEVmodeloftheformY=Xτβ+Zτα(T)+ε,ξ=X+ηwiththeidentifyingconditionE[(ε,ητ)τ]=0,Cov[(ε,ητ)η]=σ2Ip+1.Theestimatorsofinterestedregressionparametersβ,andthemodelerrorvarianceσ2,aswellasthenonparametriccomponentsα(T),areconstructed.Undersomeregularconditions,weshowthattheestimatorsoftheunknownvectorβandtheunknownparameterσ2arestronglyconsistentandasymptoticallynormalandthattheestimatorofα(T)achievestheoptimalstrongconvergencerateoftheusualnonparametricregression.Basedontheseestimatorsandasymptoticproperties,weproposetheVN,pteststatisticandempiricallog-likelihoodratiostatisticfortestingserialcorrelationinthemodel.Theproposedstatisticsareshowntohaveasymptoticnormalorchi-squaredistributionsunderthenullhypothesisofnoserialcorrelation.Somesimulationstudiesareconductedtoillustratethefinitesampleperformanceoftheproposedtests.