Partially Linear Models

Partially Linear Models

ID:40087079

大小:1.57 MB

页数:213页

时间:2019-07-20

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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

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