Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/37088
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dc.contributor.advisor宋傳欽zh_TW
dc.contributor.advisorSong, Chuan-Cinen_US
dc.contributor.author李瑋珊zh_TW
dc.contributor.authorLi, Wei-Shanen_US
dc.creator李瑋珊zh_TW
dc.creatorLi, Wei-Shanen_US
dc.date2008en_US
dc.date.accessioned2009-09-19T04:07:30Z-
dc.date.available2009-09-19T04:07:30Z-
dc.date.issued2009-09-19T04:07:30Z-
dc.identifierG0094751006en_US
dc.identifier.urihttps://nccur.lib.nccu.edu.tw/handle/140.119/37088-
dc.description碩士zh_TW
dc.description國立政治大學zh_TW
dc.description應用數學研究所zh_TW
dc.description94751006zh_TW
dc.description97zh_TW
dc.description.abstract中文摘要\n\n有限離散條件分配相容性問題可依相容性檢驗、唯一性檢驗以及找出所有的聯合機率分配三層次來討論。目前的文獻資料有幾種研究方法,本文僅分析、比較其中的比值矩陣法和圖形法。\n\n二維中,我們發現簡化二分圖的分支與IBD矩陣中的對角塊狀矩陣有密切的對應關係。在檢驗相容性時,圖形法只需檢驗簡化二分圖中的每個分支,正如同比值矩陣法只需檢驗IBD矩陣中的每一個對角塊狀矩陣即可。在檢驗唯一性時,圖形法只需檢驗簡化二分圖中的分支數是否唯一,正如同比值矩陣法只需檢驗IBD矩陣中的對角塊狀數是否唯一即可。在求所有的聯合機率分配時,運用比值矩陣法可推算出所有的聯合機率分配,但是圖形法則無法求出。\n\n三維中,本文提出了修正比值矩陣法,將比值數組按照某種索引方式在平面上有規則地呈現,可降低所需處理矩陣的大小。此外,我們也發現修正比值矩陣中的橫直縱迴路和簡化二分圖中的迴路有對應的關係,因此可觀察出兩種方法所獲致某些結論的關聯性。在檢驗唯一性時,圖形法是檢驗簡化二分圖中的分支數是否唯一,而修正比值矩陣法是檢驗兩個修正比值矩陣是否分別有唯一的GROPE矩陣。修正比值矩陣法可推算出所有的聯合機率分配。\n\n圖形法可用於任何維度中,修正比值矩陣法也可推廣到任何維度中,但在應用上,修正比值矩陣法比圖形法較為可行。zh_TW
dc.description.abstractThe issue of the compatibility of finite discrete conditional distributions could be discussed hierarchically according to the compatibility, the uniqueness, and finding all possible joint probability distributions. There are several published methods, but only the Ratio Matrix Method and the Graphical Method are analyzed and compared in this thesis. \n\nIn bivariate case, a close correspondence between the components of the reduced bipartite graph and the diagonal block matrices of the IBD matrix can be found. When we examine the compatibility, just as simply each diagonal block matrix of the IBD matrix needs to be examined using the Ratio Matrix Method, so does each component of the reduced bipartite graph using the Graphical Method. When we examine the uniqueness, just as whether the number of the diagonal blocks of the IBD matrix is unique needs to be examined, so does the number of the components of the reduced bipartite graph. The Ratio Matrix Method can provide all possible joint probability distributions, but the Graphical Method cannot. \n\nIn trivariate case, this thesis proposes a Revised Ratio Matrix Method, in which we can present the ratio array regularly in the plane according to the index and reduce the corresponding matrix size. It is also found that each circuit in the revised ratio matrix corresponds to a circuit in the reduced bipartite graph. Therefore, the relation between the results of the two methods can be observed. When we examine the uniqueness with the Graphical Method, we examine whether the number of the components in the reduced bipartite graph is unique. But with the Revised Ratio Matrix Method, we examine whether each revised ratio matrix has a unique GROPE matrix. All possible joint probability distributions can be derived through the Revised Ratio Matrix Method. \n\nThe Graphical Method can be applied to the higher dimensional cases, so can the Revised Ratio Matrix Method. But the Revised Ratio Matrix Method is more feasible than the Graphical Method in application.en_US
dc.description.tableofcontents中文摘要-----------------------------------------------------------------------------------------i\nAbstract------------------------------------------------------------------------------------------ii\n1.緒論--------------------------------------------------------------------------------------------1\n 1.1研究動機與目的---------------------------------------------------------------------1\n 1.2 研究架構-----------------------------------------------------------------------------1\n2.文獻探討--------------------------------------------------------------------------------------3\n 2.1 基礎圖論-----------------------------------------------------------------------------3\n 2.2 高維數組簡介-----------------------------------------------------------------------4\n 2.3 比值矩陣法--------------------------------------------------------------------------6\n 2.4 圖形法------------------------------------------------------------------------------14\n 2.5 比值矩陣法與圖形法之比較---------------------------------------------------26\n3.比值矩陣法(或修正比值矩陣法)與圖形法關聯性之分析-------------------------27\n 3.1 二維中比值矩陣法與圖形法關聯性之分析---------------------------------27\n 3.2 三維中之修正比值矩陣法------------------------------------------------------38\n 3.3 三維中修正比值矩陣法與圖形法關聯性之分析---------------------------49\n4.其他相容性問題---------------------------------------------------------------------------90\n5.結論---------------------------------------------------------------------------------------------------95\n參考文獻---------------------------------------------------------------------------------------98zh_TW
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dc.language.isoen_US-
dc.source.urihttp://thesis.lib.nccu.edu.tw/record/#G0094751006en_US
dc.subject相容zh_TW
dc.subject比值矩陣zh_TW
dc.subject秩1正擴張矩陣zh_TW
dc.subject不可約化塊狀對角矩陣zh_TW
dc.subject二分圖zh_TW
dc.subject圖形法zh_TW
dc.subject修正比值矩陣法zh_TW
dc.subject廣義秩1正擴張矩陣zh_TW
dc.subjectcompatibilityen_US
dc.subjectratio matrixen_US
dc.subjectROPE matrixen_US
dc.subjectIBD matrixen_US
dc.subjectbipartite graphen_US
dc.subjectGraphical Methoden_US
dc.subjectRevised Ratio Matrix Methoden_US
dc.subjectGROPE matrixen_US
dc.title有限離散條件分配族相容性之研究zh_TW
dc.titleA study on the compatibility of the family of finite discrete conditional distributions.en_US
dc.typethesisen
dc.relation.reference\\bibitem{Arnold1989}Arnold, B. C. and Press, S. J. (1989), Compatible conditional distributions. \\textit{J. Amer. Statist. Assoc.}, \\textbf{84}, 152-156.zh_TW
dc.relation.reference\\bibitem{Arnold2004}Arnold, B. C., Castillo,E., and Sarabia, J. M. (2004), Compatibility of partial or complete conditional probability specifications. \\textit{J. Statist. Plann. Inference}, \\textbf{123}, 133-159.zh_TW
dc.relation.reference\\bibitem{Kuo2008}Kuo, K. L. (2008), \\textit{New tools for studying the Ferguson-Dirichlet process and compatibility of a family of conditionals.},政治大學應用數學系博士論文。zh_TW
dc.relation.reference\\bibitem{Minc1988}Minc, H. (1988), \\textit{Nonnegative Matrices}. New York: Wiley.zh_TW
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dc.relation.reference\\bibitem{Rossman1995}Rossman, Allan J. and Short, Thomas H. (1995), Conditional probability and education reform:Are they compatible? \\textit{Journal of Statistics Education}, \\textbf{v.3, n.2}.zh_TW
dc.relation.reference\\bibitem{Slavkovic2004}Slavkovic, A. B. (2004), \\textit{Statistical Disclosure Limitation Beyond the Margins.} Ph.D. Thesis, Department of Statistics, Carnegie Mellon University, 2004.zh_TW
dc.relation.reference\\bibitem{Slavkovic2006}Slavkovic, A. B. and Sullivant, S. (2006), The space of compatible full conditionals is a unimodular toric variety.\\textit{Journal of Symbolic Computation}, \\textbf{41}(2), 196-209.zh_TW
dc.relation.reference\\bibitem{Song2009}Song, C. C., Li, L. A., Chen, C. H., Jiang, T. J., and Kuo, K. L. (2009), Compatibility of finite discrete conditional distributions.\\textit{Statistica Sinica.}(Accepted) To appear.zh_TW
dc.relation.reference\\bibitem{Tucker2002}Tucker, A. (2002), \\textit{Applied combinatorics}. John Wiley \\& Sons.zh_TW
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