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研究生: 彭綉媛
論文名稱: 雙邊冪分配參數估計問題的研究
A parameter estimation method for the two-sided power distribution
指導教授: 張延彰
洪文良
口試委員:
學位類別: 碩士
Master
系所名稱: 南大校區系所調整院務中心 - 應用數學系所
應用數學系所(English)
論文出版年: 2010
畢業學年度: 98
語文別: 中文
論文頁數: 24
中文關鍵詞: 雙邊冪分配Beta分配三角分配EM演算法
外文關鍵詞: two-sided power distribution, Beta distribution, triangular distribution, EM algorithm
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  • 摘 要
    這幾年來雙邊冪分配逐漸受到重視,像van Dorp和Kotz(2002a)及Nadarajah(2003)的研究對雙邊冪分配都有詳細的說明。和傳統三角分配相比,雙邊冪分配使用上彈性較大;和Beta分配相比,其機率值的計算比較容易。在討論參數估計的問題時,如van Dorp和Kotz(2002a)及Nadarajah(2003)都假設雙邊的形狀是一樣的,Herrerias,et al.(2009)除了詳細介紹雙邊冪分配的性質之外,也提出一個遞迴求解的方式進行估計。在該篇文章中,也提到雙邊冪分配可以用混合模式來呈現。本文將利用此混合模式建立一雙邊冪分配的演算法,並以數值模擬來說明我們的方式。


    Abstract

    In recent years, the two sided power distribution is valued gradually. Such as van Dorp, Kotz (2002a) or Nadarajah (2003) detailed the two sided power distribution in their research. Compared with the traditional triangular distribution, using the two sided power distribution is more flexible; and distribution compared with Beta, the calculation of its probability value is easier. In the discussion of parameter estimation, van Dorp, Kotz(2002a) and Nadarajah(2003) assumed that the shape of both sides is equal. The Herrerias,et al.(2009) not only introduced the property of the two sided power distribution in detail, but also propose a algorithm solving approach to estimate. In this article, it also mentioned that the two sided power distribution can be presented by using mixed-model. This article will use the mixed-model to build a two sided power distribution algorithm and explain our ways with the number emulation.

    目 錄 1. 中文摘要 I 2. 英文摘要 II 3. 目錄 III 4. 第一章 緒論 1 5. 第二章 雙邊冪分配的基本性質 3 6. 第三章 演算法 13 7. 第四章 數值例子 18 8. 第五章 結論 23 9. 參考文獻 24

    參考文獻

    [1] J.R van Dorp and S. Kotz, The standard two sided power distribution and its properties: with applications in financial engineering, Am. Stat. 56 (2) (2002a),
    pp. 90-99.

    [2] J.R. van Dorp and S. Kotz, A novel extension of the triangular distribution and its parameter estimation, Statistician 56 (2) (2002a), pp. 63-79.

    [3] M.A. Johnson and M.R. Taaffe, An investigation of phase-type distribution moment-matching algorithms for use in queuing models, Queuing Syst. 8 (1) (1991), pp. 129-147.

    [4] D. Karlis and E. Xekalaki, Improving the EM algorithm for mixtures, Stat. Comput. 9 (4) (1999), pp. 303-307.

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