| 研究生: |
陳世傑 Chen, Shih Chieh |
|---|---|
| 論文名稱: |
離散條件機率分配之相容性研究 On compatibility of discrete conditional distributions |
| 指導教授: |
姚怡慶
Yao, Yi Ching |
| 學位類別: |
博士
Doctor |
| 系所名稱: |
商學院 - 統計學系 Department of Statistics |
| 論文出版年: | 2015 |
| 畢業學年度: | 103 |
| 語文別: | 英文 |
| 論文頁數: | 59 |
| 中文關鍵詞: | 條件機率分配之相容性 、圖論 、相連性 、展開樹 、吉布斯抽樣法 、蒙地卡羅馬可夫鏈法 |
| 外文關鍵詞: | compatibility of conditional distributions, graph theory, connectedness, spanning tree, Gibbs sampler, MCMC |
| 相關次數: | 點閱:36 下載:6 |
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設二個隨機變數X1 和X2,所可能的發生值分別為{1,…,I}和{1,…,J}。條件機率分配模型為二個I × J 的矩陣A 和B,分別代表在X2 給定的條件下X1的條件機率分配和在X1 給定的條件下X2的條件機率分配。若存在一個聯合機率分配,而且它的二個條件機率分配剛好就是A 和B,則稱A和B相容。我們透過圖形表示法,提出新的二個離散條件機率分配會相容的充分必要條件。另外,我們證明,二個相容的條件機率分配會有唯一的聯合機率分配的充分必要條件為:所對應的圖形是相連的。我們也討論馬可夫鏈與相容性的關係。
For two discrete random variables X1 and X2 taking values in {1,…,I} and {1,…,J}, respectively, a putative conditional model for the joint distribution of X1 and X2 consists of two I × J matrices representing the conditional distributions of X1 given X2 and of X2 given X1. We say that two conditional distributions (matrices) A and B are compatible if there exists a joint distribution of X1 and X2 whose two conditional distributions are exactly A and B. We present new versions of necessary and sufficient conditions for compatibility of discrete conditional distributions via a graphical representation. Moreover, we show that there is a unique joint distribution for two given compatible conditional distributions if and only if the corresponding graph is connected. Markov chain characterizations are also presented.
1 Introduction 1
2 Compatible conditional distributions 5
2.1 Compatibility ......................... 5
2.2 Review of the ratio matrix approach for
compatibility between two conditional
distribution .......................... 7
3 Graphical representation approach 14
3.1 Graphical representation ............. 14
3.2 Compatibility of a ratio set R and
characterization of probability
distributions satisfying R ........... 19
3.3 The relation between the ratio matrix
approach and graphical representation
approach ............................. 26
4 Markov chain characterizations 31
4.1 Compatibility by the Gibbs sampler ... 31
4.2 Simulations .......................... 49
5 Conclusions 55
References 57
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