Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/90189
DC FieldValueLanguage
dc.contributor.advisor宋傳欽zh_TW
dc.contributor.author徐惠莉zh_TW
dc.creator徐惠莉zh_TW
dc.date1990en_US
dc.date1989en_US
dc.date.accessioned2016-05-03T06:17:40Z-
dc.date.available2016-05-03T06:17:40Z-
dc.date.issued2016-05-03T06:17:40Z-
dc.identifierB2002005454en_US
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/90189-
dc.description碩士zh_TW
dc.description國立政治大學zh_TW
dc.description應用數學系zh_TW
dc.description.abstract(一) Smith & Sedransk ( 1982 )利用雙重抽樣方法研究魚群年齡組成,給定第一階段樣本數nν及其分配nv= (n1ν,...., n1ν),說明如何選取最佳的貝氏子樣本數分配n0∞=( n01∞,...,n01∞), 使得近似風險函數r∞ (nν, nν, n0∞)最小,而後Jinn. Smithzh_TW
dc.description.tableofcontents第一章 緒論...................................1\r\n第二章 文獻回顧\r\n第一節 引言...................................3\r\n第二節 定義符號與基本假設...................................4\r\n第三節 最佳子樣本數的演算法...................................6\r\n第四節 兩種求A (nν)的方法...................................9\r\n第三章 求第一階段樣本數的方法\r\n第一節 引言...................................12\r\n第二節 期望值近似法...................................15\r\n第三節 電腦模擬期望值近似法...................................22\r\n第四節 電腦模擬近似法...................................25\r\n第四章 常態分配近似法\r\n第一節 引言................................... 28\r\n第二節 公式之推導...................................30\r\n第五章 有關解的一些性質\r\n第一節 引言...................................43\r\n第二節 公式之推導...................................44\r\n參考文獻...................................61\r\n附錄...................................66zh_TW
dc.source.urihttp://thesis.lib.nccu.edu.tw/record/#B2002005454en_US
dc.title兩相分層抽樣中貝氏最佳解的特例zh_TW
dc.typethesisen_US
dc.relation.reference<註1> Cochran ,W. G. (1977).\r\nSampling Techniques , 3rd edition 327 - 328. New York:Wiley.\r\n<註2> Smith.P.J. and Sedransk.J. (1982).\r\nBayesian Optimization of Estimation of the Age Composition of a Fish Population. \r\nJournal of American Statistical Association 77. 707 - 713.\r\n<註3> J.H.Jinn, J.Sedransk and Philip Smith (1987) \r\nOptimal Two-Phase Stratified Sampling f or Estimation of the Age Composition of a Fish Position.\r\nBIOMERTICS 43. 343 - 353.\r\n<註4 > poststratification variable. 在實驗前母體無法被分層,因此可在第一階段抽樣後,利用這個變數觀察所抽取的樣本,將母體分層,因此為一輔助變數。\r\n<註5>因為\r\nfν ({ n1 }∣nν , { P1 }) f ({P1 }∣{b1})=( nν)!Γ(b.)█(I@π@i=1)^ [\" \" ?P_1?^(n^ν+b-1)/(?n_(?n_1?^ν )?^ν !Γ(b1))]\r\n所以\r\ng({n1ν}∣nν)\r\n=∫??(n^ν ?)! Γ(b.) █(I@π@i=1)^ [\" \" ?P_1?^(n^ν+b-1)/(?n_(?n_1?^ν )?^ν !Γ(b1))] dP\r\n=((n^ν)! Γ(b.) )/(?π^2?_(i=1) ?? n?_1?^ν∣Γ(b1)) ∫?█(I@π@i=1)^ ?P_1?^(n^ν+b-1) dP\r\n=((n^ν)! Γ(b.) )/(?π^2?_(i=1) ?? n?_1?^ν∣Γ(b1)) (?π^2?_(i=1) ??Γ( n?_1?^ν+b1))/( Γ(n^ν+b.) )\r\n所以\r\nf’’({P1},I nν,{ n1})\r\n=(f^ν ({ n_1 }∣n^(ν ) ,{ P_1 }) f ({P_1 }∣{b_1}))/(g({ ?n_1?^ν }∣n^(ν ) )\r\n=Γ(nν+b.) █(I@π@i=1)^ [\" \" ?P_1?^(n^ν+b-1)/(Γ(n^ν+b.))]\r\n<註6 >矩陣k 表研究者對於不同母體的重視程度.若對所有母體均有相等的重視,則取kjj =1 j一般視研究的目的來選取{kjj}.\r\n<註7>梁淑真.(1989). 雙重抽樣之貝氏最佳樣本與子樣本數選取的特例. P9.\r\n<註8>DEGROOT,MORRIS H.(1970).\r\nOptimal Statistical Decision. P234.\r\nNew York:McGraw-Hill.\r\n<註9 > Rao , J.N.K, and Ghangurde , P.D. (1972) \r\nBaysian Optimization in Sampling Finite Populations. Journal of the American Statistical Association 67.439 - 443.\r\n<註10>同<註7>, P19-P35.\r\n<註11>同<註7>,P28, P35.\r\n<註12>由<註5>知,當I=2, f’’({P1},I nν,{ n1})為Beta分配,所以\r\nE’’(P12)=∫P12Γ(n^ν+b.) █(I@π@i=1)^ [\" \" ?P_1?^(n^ν+b-1)/(?n_(?n_1?^ν )?^ν !Γ(b1))] dP1\r\n=( ( ?n_1?^ν ?+ b?_1)(?n_1?^ν+b_1+1))/( (n^ν+b.)(n^ν+b.+1))\r\nI=1,2.\r\n<註13> (3.3.1)式的f’(n1∣nν,P1)與(2.2.6)式的g(n1ν∣nν)機率分配的圖形比較,較為陡峭的為前者,較為平緩的為後者.\r\n<註14>Tom M. Apostol.(1977)\r\nMathematical Analysis. 2nd edition. 354-355.\r\n<註15>同<註7>,P36-P45.zh_TW
item.openairetypethesis-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_46ec-
item.cerifentitytypePublications-
item.grantfulltextopen-
Appears in Collections:學位論文
Files in This Item:
File SizeFormat
index.html115 BHTML2View/Open
Show simple item record

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.