非參數(shù)密度估計(jì)在判別分析中的應(yīng)用.pdf

1、南京信息工程大學(xué)碩士學(xué)位論文非參數(shù)密度估計(jì)在判別分析中的應(yīng)用姓名：朱干江申請(qǐng)學(xué)位級(jí)別：碩士專業(yè)：應(yīng)用數(shù)學(xué)指導(dǎo)教師：王桂芝20070501AbstractThenonparametricestimationofthedensityfunctionisanimportantdirectionformodernstatisticsdevelopmentinrecentlymost20yearswtfichvariesthepatternoft

2、hetraditionalstatisticsdevelopmentThedensityfunctioncanbenon—pa跏metriclyestimatedthroughmanyways，mainlybytherectangle，theRosenblatt’theParzenkcmelandthenearestneighborBythedevelopmentofcomputertechnologytheapplicationtha

3、tbasedonthenonparametricestimationovercomesthepuzzlessuchasthenonparametricestimation’Stheoryonbigsample，theapplicationbaSedonbigdataandthecomplexoperation；beginstOinvolvemorcandmorefields，ie：socialsciences，physics，biolo

4、gyandengineeringandtechniqueWhythenonparametricestimationisimportantBecauseitCanbeappliednotonlyalonebutalsobythemiddlelinkofstatisticsinference，suchasthenonparametricdiscriminantanalysis，assembleanalysisandimitatingrand

5、omfigureAccordingtotheindexoffouraSpects0)ayoffabilityrefundabilitydevelopmentalabilityfumncelevel)ofacompanycomingintothemarkettheestimationtoitsfinancialstatusinthesecuritiesbusinessisveryimportanttothein_terestgroup，e

6、speciallytothemostinvestorsbyjudgingwhetherthelosswillSTandNSTThispaperdctalledlyintroducekernelofprobabilitydensitybig—sampletheroyofnearestneighboringestimate，academicbasisofnonparameteriediscriminanceandprincipleofnon