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研究生:劉嘉樺
研究生(外文):Chia-hua Liu
論文名稱:關於某些條件期望值的刻劃
論文名稱(外文):Some Characterization Results Based on Certain Conditional Expectations
指導教授:黃文璋黃文璋引用關係
指導教授(外文):Wen-Jang Huang
學位類別:碩士
校院名稱:國立高雄大學
系所名稱:統計學研究所
學門:數學及統計學門
學類:統計學類
論文種類:學術論文
論文出版年:2006
畢業學年度:94
語文別:英文
論文頁數:23
中文關鍵詞:Beta分佈刻劃常數迴歸條件期望值gamma分佈混合分佈
外文關鍵詞:Beta distributioncharacterizationconstant regressionconditional expectationgamma distributionmixture distributions
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給定$X$,$Y$為二獨立且非退化的隨機變數,Lukacs (1995) 證明 $X/(X+Y)$ 和 $X+Y$ 獨立,若且唯若 $X$,$Y$ 均有 gamma 分佈,且有相同的尺度參數。
本文中,在 $X/U$ 和 $U$ 獨立且 $X/U$ 為 ${\mathcal Be}(p,q)$ 分佈的假設之下,我們利用 $E(h(U,X)|X)\\=b$ 的條件來刻劃 $(U,X)$ 的分佈。其中,$h$ 被允許為 $U-X$ 的指數函數或是 $U-X$ 的三角函數。我們的結果之一是: 假如 $q=1$,且對於某一正整數 $n$,$E(\sum_{i=1}^n e^{i(U-X)}|X)=b$,其中 $b$ 為一常數,則 $(U,X)$ 的分佈可以決定。一些相關的其他結果也將被提出。
Given two independent non-degenerate positive random variables $X$ and $Y$, Lukacs (1955) proved that $X/(X+Y)$ and $X+Y$ are independent if and only if $X$ and $Y$ are gamma distributed with the same scale parameter.
In this work, under the assumption $X/U$ and $U$ are independent, and $X/U$ has a ${\mathcal Be}(p,q)$ distribution, we characterize the distribution of $(U,X)$ by the condition $E(h(U,X)|X)=b$, where $h$ is allowed to be an exponential function or trigonometric function of $U-X$. Among others, we prove if $q=1$, and for some positive integer $n$, $E(\sum_{i=1}^n e^{i(U-X)}|X)=b$, where $b$ is a constant, then the distribution of $(U,X)$ can be determined. Some other related results are also presented.
中文摘要 .......................... ii
英文摘要 ......................... iii
1. Introduction .................... 1
2. Preliminaries ................... 2
3. Main results .................... 3
4. Conclusion ..................... 16
References ........................ 17
小傳 .............................. 18
1. Bobecka, K. and Wesolowski, J. (2002). Three dual regression schemes for the Lukacs theorem. Metrika 56, 43-54.
2. Bolger, E.M. and Harkness, W.L. (1965). A characterization of some distributions by conditional moments. Ann. Math. Stat. 36, 703-705.
3. Chou, C.W. and Huang, W.J. (2003). Characterizations of the gamma distribution via conditional moments. Sankhya 65, 271-283.
4. Gupta, A.K. and Wesolowski, J. (1997). Uniform mixtures via posterior means. Ann. Inst. Stat. Math. 49, 171-180.
5. Gupta, A.K. and Wesolowski, J. (2001). Regressional identifiability and identification for beta mixtures. Statistics & Decisions 19, 71-82.
6. Hall, W.J. and Simons, G. (1969). On characterizations of the gamma distribution. Sankhya A 31, 385-390.
7. Huang, W.J. and Chang, S.H. (2005). On some characterizations of the mixture of gamma distributions. Technical Report, Department of Applied Mathematics, National Kaohsiung University.
8. Huang, W.J. and Chou, C.W. (2004). Characterizations of the gamma distribution via conditional expectations. Technical Report, Department of Applied Mathematics, National Kaohsiung University.
9. Huang, W.J. and Su, J.C. (1997). On a study of renewal process connected with certain conditional moments. Sankhya A 59, 28-41.
10. Huang, W.J. and Wong, H.L. (1998). On a study of beta and geometric mixtures by conditional moments. Technical Report, Department of Applied Mathematics, National Sun Yat-sen University.
11. Li, S.H., Huang, W.J. and Huang, M.N.L. (1994). Characterizations of the Poisson process as a renewal process via two conditional moments. Ann. Inst. Stat. Math. 46, 351-360.
12. Lukacs, E. (1955). A characterization of the gamma distribution. Ann. Math. Stat. 26, 319-324.
13. Wesolowski, J. (1989). A characterization of the gamma process by conditional moments. Metrika 36, 299-309.
14. Wesolowski, J. (1990). A constant regression characterization of the gamma law. Adv. Appl. Prob. 22, 488-490.
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