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《Partially Linear Models》由會員上傳分享，免費在線閱讀，更多相關(guān)內(nèi)容在學術(shù)論文-天天文庫。
1、PARTIALLYLINEARMODELSWolfgangH?ardleInstitutf?urStatistikundOkonometrie?Humboldt-Universit?atzuBerlinD-10178Berlin,GermanyHuaLiangDepartmentofStatisticsTexasA&MUniversityCollegeStationTX77843-3143,USAandInstitutf?urStatistikundOkonometrie?Humboldt-Universit?atzuBerlinD-10178Berlin,GermanyJiti
2、GaoSchoolofMathematicalSciencesQueenslandUniversityofTechnologyBrisbaneQLD4001,AustraliaandDepartmentofMathematicsandStatisticsTheUniversityofWesternAustraliaPerthWA6907,AustraliaiiInthelasttenyears,therehasbeenincreasinginterestandactivityinthegeneralareaofpartiallylinearregressionsmoothingi
3、nstatistics.Manymethodsandtechniqueshavebeenproposedandstudied.Thismonographhopestobringanup-to-datepresentationofthestateoftheartofpartiallylinearregressiontechniques.Theemphasisofthismonographisonmethodologiesratherthanonthetheory,withaparticularfocusonapplicationsofpartiallylinearregressio
4、ntechniquestovariousstatisticalproblems.Theseproblemsincludeleastsquaresregression,asymptoticallyecientestimation,bootstrapresampling,censoreddataanalysis,linearmeasurementerrormodels,nonlinearmeasurementmodels,nonlinearandnonparametrictimeseriesmodels.Wehopethatthismonographwillserveasausef
5、ulreferencefortheoreticalandappliedstatisticiansandtograduatestudentsandotherswhoareinterestedintheareaofpartiallylinearregression.Whileadvancedmathematicalideashavebeenvaluableinsomeofthetheoreticaldevelopment,themethodologicalpowerofpartiallylinearregressioncanbedemonstratedanddiscussedwith
6、outadvancedmathematics.Thismonographcanbedividedintothreeparts:partone{Chapter1throughChapter4;parttwo{Chapter5;andpartthree{Chapter6.Inthe rstpart,wediscussvariousestimatorsforpartiallylinearregressionmodels,establishtheo-reticalresultsfortheestimators,proposeestimationprocedures,andimplemen
7、ttheproposedestimationproceduresthroughrealandsimulatedexamples.Thesecondpartisofmoretheoreticalinterest.Inthispart,weconstructseveraladaptiveandecientestimatesfortheparametriccomponent.WeshowthattheLSestimatoroftheparametriccomponentcanbemo
