rss下pareto分布参数的优良估计

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1、吉首大学硕士学位论文RSS下Pareto分布参数的优良估计钱文舒二0一八年五月分类号密级公开UDC单位代码吉首大学硕士学位论文RSS下Pareto分布参数的优良估计ParameterestimationofParetodistributionbasedonRankedsetsampling研究生姓名钱文舒指导教师方东辉（教授）副指导教师陈望学（博士）学科专业统计学研究方向抽样设计与统计计算提交论文日期年月日论文答辩日期年月日答辩委员会主席论文评阅人二0一八年五月2xml3+0Pareto
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',ojT,XojT,%`Gg#iABSTRACTABSTRACTInthisarticle,weareinterestedinestimationofthescaleandtheshapepa-rametersforparetodistributionp(θ,α).Simplerandomsampling(SRS),rankedsetsampling(RSS),e

15、xtremeRSS(ERSS)andmedianRSS(MRSS)willbeused.Anunbiasedestimator(UE),amodifiedUE(MUE),thebestlinearunbiasedestima-tor(BLUE(s)),themodifiedBLUE(s)(MBLUE(s))andadhocestimators(AHEs)ofθandαfromp(θ,α)willberespectivelystudiedincaseswhenoneparameterisknownandwhenbothareunknown.Wecomparet

16、heseestimatorsunderperfectandimperfectranking.Inthefollowing,letusintroducethecontentsofeachchapterinbrief.Chapter1summarizessomerelatedbackgroundofParetodistribu-tionandrankedsetsampling,andthemainworkandinnovationofthisdissertation.Chapter2mainlystudiestheparameterestimationofP

17、aretodistri-butionbasedonRSS.SeveralestimatorsofthescaleandshapeparametersfromparetodistributionwillbeconsideredincaseswhenoneparameterisknownandwhenbothareunknownunderRSS.TheseestimatorscontainsUE,MUE,BLUE(s),MBLUE(s)andAHEs.Chapter3mainlystudiestheparameterestimationofParetodis

18、tri-butionbasedonERSS.Severalestimatorso