English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113656/144643 (79%)
Visitors : 51736386      Online Users : 631
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大機構典藏 > 理學院 > 應用數學系 > 學位論文 >  Item 140.119/32578
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/32578


    Title: 分析失去部分訊息的貝氏更新計算方法
    Bayesian updating methods for the analysis of censored data.
    Authors: 范靜宜
    Fan, Gin-Yi
    Contributors: 姜志銘
    范靜宜
    Fan, Gin-Yi
    Keywords: 貝氏
    準貝氏法
    平均變異數和
    吉氏取樣器
    Bayes
    quasi-Bayes
    Average variance sum
    Gibbs sampler
    Date: 2006
    Issue Date: 2009-09-17 13:47:06 (UTC+8)
    Abstract: 對於使用貝氏法來處理部份區分(partially-classified)或是失去部分訊息資料的類別抽樣(categorical sampling with censored data),大多建立在「誠實回答」(truthful reporting)以及「無價值性失去部分訊息」(non-informative censoring)的前提下。Jiang(1995)及Jiang and Dickey(2006)取消以上兩個限制,提出貝氏解並利用準貝氏法(quasi-Bayes)來求近似解,而Jiang and Ko(2004)也利用吉氏取樣器(Gibbs sampler)來近似這類問題的貝氏解。本文首先嘗試利用Kuroda, Geng and Niki(2001)所提的“平均變異數和(average variance sum)”估計法
    來應用到我們問題的貝氏解。在小樣本時,數值上我們可求得貝氏解,因此本文另一個重點為在小樣本時比較以上三種方法估計值的準確性,並考慮先驗參數(prior)的選取對估計的影響。
    本文更進一步證明若選取到某種特殊的先驗參數時,利用“平均變異數和”的方法所計算出來的結果會和
    準貝氏法的估計結果相同,而且皆等於用貝氏法計算出的結果。
    Reference: [1] Casella, G., and George, E. I. (1992). "Explaining the Gibbs Sampler," The American Statistician, 46, 167-174.
    [2] Dickey, J. M., Jiang, T. J., and Kadane, J. B. (1987). "Bayesian Methods for Censored Categorical Data," Journal of the American Statistical Association, 82, 773-781.
    [3] Gelfand, A. E., and Smith, A. F. M. (1990). "Sampling-Based Approaches to Calculating Marginal Densities," Journal of the American Statistical Association, 85, 398-409.
    [4] Hastings, W. K. (1970). "Monte Carlo Sampling Methods Using Markov Chains and their Application,"Biometrika, 57, 97-109.
    [5] Jiang, T. J. (1995), "Quasi-Bayes Sequential Method for Categorical Data Under Informative Censoring,"Technical Report, 1995-02, Dept. of Mathematical Sciences, National Chengchi University.
    [6] Jiang, T. J., and Dickey, J. M. (2006), "Quasi-Bayes Methods for Categorical Data Under Informative Censoring," to be published.
    [7] Jiang, T. J., Kadane, J. B., and Dickey, J. M. (1992), "Computation of Carlson`s Multiple Hypergeometric Function for Bayesian Applications," Journal of Computational and Graphical Satatistics, 1, 231-251.
    [8] Jiang, T. J., and Ko, Li-Wen (2004), "The Gibbs Sampler for Bayesian Analysis on Censored Categorical Data," 2004 Proceeding of the Section on Bayesian Statistical Science of the American Statistical Assocition, 97-103.
    [9] Karson, M. J., and Wrobleski, W. J. (1970), "A Bayesian Analysis of Binomial Data with a Partially Informative Category," in Proceedings of the Bussiness and Economic Statistics Section, American Statistical Association, 523-534.
    [10] Kuroda, M., Geng, Z., and Niki, N. (2001) "Bayesian Sequential Learning from Incomplete Data on Decomposable Graphical Models," Journal of the Japanese Society of Computational Statistics, 14, 11-29.
    [11] Geman, S., and Geman, D. (1984), "Stochastic Relation, Gibbs Distribution and the Bayesian Restortion of Image," IEEE Transactions on Pattern Analysis and Machine Intelligence, 6, 721-741.
    [12] 汪為開(1995), "失去部份訊息而有價值的類別資料依循序程序處理之計算方法,"碩士論文-國立政治大學應用數學系研究所.
    [13] 柯力文(2003), "準貝氏法與吉氏取樣器在處理失去部分訊息資料上的比較,"碩士論文-國立政治大學應用數學系研究所.
    [14] 羅文宜(2005), "具有訊息的遺失資料計算方法之比較,"碩士論文-國立政治大學應用數學系研究所.
    Description: 碩士
    國立政治大學
    應用數學研究所
    93751011
    95
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0093751011
    Data Type: thesis
    Appears in Collections:[應用數學系] 學位論文

    Files in This Item:

    File Description SizeFormat
    75101101.pdf44KbAdobe PDF2945View/Open
    75101102.pdf60KbAdobe PDF2918View/Open
    75101103.pdf101KbAdobe PDF2866View/Open
    75101104.pdf213KbAdobe PDF2883View/Open
    75101105.pdf417KbAdobe PDF2802View/Open
    75101106.pdf400KbAdobe PDF2801View/Open
    75101107.pdf526KbAdobe PDF2851View/Open
    75101108.pdf439KbAdobe PDF2877View/Open
    75101109.pdf441KbAdobe PDF2876View/Open
    75101110.pdf394KbAdobe PDF2867View/Open
    75101111.pdf346KbAdobe PDF2750View/Open
    75101112.pdf226KbAdobe PDF21373View/Open
    75101113.pdf147KbAdobe PDF21170View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback