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Springer.Applied.Nonparametric.Regression.(Springer.1994)

Springer.Applied.Nonparametric.Regression.(Springer.1994)

ID：34860787

大小：4.42 MB

页数：433页

时间：2019-03-12

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1、AppliedNonparametricRegressionWolfgangH•ardleHumboldt-Universit•atzuBerlinWirtschaftswissenschaftlicheFakult•atInstitutf•urStatistikundOkonometrie•SpandauerStr.1D{10178Berlin1994F•urRenateNoraViolaAdrianContentsIRegressionsmoothing11Introduction31.1Mo

2、tivation.....................................71.2Scopeofthisbook................................142Basicideaofsmoothing172.1Thestochasticnatureoftheobservations....................262.2Hurdlesforthesmoothingprocess........................273Smoothingt

3、echniques313.1KernelSmoothing.................................323.2Complements...................................493.3ProofofProposition...............................493.4k-nearestneighborestimates...........................523.5Orthogonalseriesestim

4、ators...........................613.6Splinesmoothing.................................703.7Complements...................................773.8Anoverviewofvarioussmoothers........................783.9Recursivetechniques...............................783

5、.10Theregressogram.................................803.11Acomparisonofkernel,k-NNandsplinesmoothers..............87IIThekernelmethod1114Howcloseisthesmoothtothetruecurve?1134.1Thespeedatwhichthesmoothcurveconverges................1164.2Pointwisecon de

6、nceintervals..........................1254.3Variabilitybandsforfunctions..........................1394.4Behaviorattheboundary............................1594.5Theaccuracyasafunctionofthekernel....................1624.6Biasreductiontechniques..........

7、..................1725Choosingthesmoothingparameter1795.1Cross-validation,penalizingfunctionsandtheplug-inmethod.........1805.2Whichselectorshouldbeused?.........................2005.3Localadaptationofthesmoothingparameter.................2145.4Compar

8、ingbandwidthsbetweenlaboratories(canonicalkernels).......2236Datasetswithoutliers2296.1Resistantsmoothingtechniques.........................2316.2Complements...................................2417Nonparametricregressiontechniquesfortimeseries2

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