r&s-plus functions help files nonparametric functional data analysis

《r&s-plus functions help files nonparametric functional data analysis》由会员上传分享，免费在线阅读，更多相关内容在工程资料-天天文库。

1、Fr´ed´ericFerratyandPhilippeVieuR/S-plusFunctionsHelpFilesNonParametricFunctionalDataAnalysisJune2,2006ContentsIntroduction...................................................11IndexesofR/S-plusroutines...............................31.1AlphabeticalIndexforal

2、lroutines.........................31.2IndexbyCategory.......................................61.2.1classifyingasampleofcurves(clustering).............61.2.2discriminatingasampleofcurves(supervisedclassification).....................................61.2.3Kernel

3、functions/integratedkernelfunctions..........61.2.4PredictingascalarresponsefromcurvesorForecastingtimeseries........................................71.2.5Preprocessingfunctionaldata.......................81.2.6Proximitiesbetweencurves(semi-metrics).........

4、...82HelpFilesformainroutines...............................92.1Introductionandnotations...............................92.2Helpfilesinalphabeticalorder............................10Index..........................................................25IntroductionT

5、hispartproposesindexesandhelpfilesfortheR/S-plusroutinesneededforimplementingNonParametricFunctionalDataAnalysis(NPFDA).Asyouwillsee,twokindsofindexesareavailable(thefirstcorrespondstothestan-dardalphabeticalorderwhereasthesecondislistedbycategory).Afterthen,t

6、hereaderwillfindhelpfilesforthemainroutines.Copyright:Youmaydownloadmaterialsfreelyforyourownpersonalstudy.Useforanycommercialpurposeisforbidden.1IndexesofR/S-plusroutines1.1AlphabeticalIndexforallroutinesapprox.fourierFourierapproximationofcurvesapprox.spline

7、.derivB-splineapproximationofthesuccessivederivativesofasetcurvesapprox.splineB-splineapproximationofasetofcurvesclassif.bwComputesabandwidthamongafixedsequenceofbandwidths(classification)classif.hiReturnsanHeterogeneityIndex(HI)forasetofcurves(classification)c

8、lassif.npfdaPerformsthenonparametricunsupervisedclassification(orclustering)methodofasampleofcurvesclassif.partFromasetofcurves,performsapartitionandcomputesthecorrespondingsplittingscore(classifi