政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/32584
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文筆數/總筆數 : 113324/144300 (79%)
造訪人次 : 51129700      線上人數 : 866
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    政大機構典藏 > 理學院 > 應用數學系 > 學位論文 >  Item 140.119/32584
    請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/32584


    題名: 運用Dirichlet過程估計卜瓦松均數
    作者: 林書淵
    貢獻者: 姜志銘
    林書淵
    關鍵詞: 無母數經驗貝氏估計法
    日期: 2006
    上傳時間: 2009-09-17 13:47:48 (UTC+8)
    摘要: 以往利用貝氏方法估計卜瓦松均數,為了計算的可行性,大多用伽碼分配(卜瓦松的共軛分配)當成均數的先驗分配,且先驗分配以經驗貝氏法來估計(母數經驗貝氏法),然而在卜瓦松均數背離伽碼分配的狀況下,估計效果並不佳。Laird (1978)提出無母數最大概似先驗分配估計法,提供卜瓦松均數之先驗分配另一選擇。當均數不具伽碼分配而集中在某些值時,此法有很好的估計效果;但在均數分散(變異數大)的狀況下,估計效果並不理想。由於在大多數的情況下,我們無法確定均數分配的型式,因此無從判定用何種估計方法較為妥當。本文首先嘗試用Escobar (1994)所提出的Dirichlet過程估計法來估計卜瓦松均數,並由模擬結果得知,不論均數之型態為伽碼分配或少數幾個值的離散分配,Dirichlet過程估計法的效果總是介於無母數最大概似估計法及母數經驗貝氏法之間,並趨向其中較好的估計法。
    In the past, when using the Bayesian method to estimate Poisson means, we used to choose conjugate prior distribution for computational simplicity, and we also empirically estimated the prior of the means Gamma distribution (PEB). However, if the true distribution of the means departs from Gamma distribution, PEB method is not very efficient. Laird (1978) estimated the prior distribution by nonparametric maximum likelihood (NPML), which provided another choice of the prior distribution. When the means are clustered in few values instead of having Gamma distribution, NPML method is very efficient, but when the means are very disperse, the method is not efficient. Because, most of the time, we do not know the true distribution of the means, it is hard to decide whether to use PEB or NPML method. This research first try to estimate Poisson means by Dirichlet Process (DP) method which is developed by Escobar (1994). According to our simulation study, whether the distribution of the means is Gamma distribution or discrete distribution having few values, DP method is as good as PEB method when PEB method is better than NPML method, and it is as good as NPML method when NPML method is better.
    參考文獻: Antoniak, C. E. (1974). ""Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems,`` The Annals of Statistics, 2, 1152-1174.
    Archibald, E. E. A. (1948). ""Plant Populations I. A New Application of Neyman`s Contagious Distribution,`` Annals of Botany, 12, 221-235.
    Blackwell, D., and MacQueen, J.B. (1973). ""Ferguson Distribution via Polya Urn Schemes,`` The Annals of Statistics, 1, 353-355.
    Escobar, M. D. (1994). ""Estimating Normal Means with a Dirichlet Process Prior,`` Journal of the American Statistical Association, 89, 268-277.
    Escobar, M. D. (1995). ""Nonparametric Bayesian Methods in Hierarchical Models,`` Journal of Statistical Planning and Inference, 43, 97-106.
    Ferguson, T. S. (1973). ""A Bayesian Analysis of Some Nonparametric Problems,`` The Annals of Statistics, 1, 209-230.
    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.
    Laird, N. M. (1978). ""Nonparametric Maximum Likelihood Estimation of a Mixing Distribution,`` Journal of the American Statistical Association, 73, 805-811.
    Robbins, H. (1955). ""An Empirical Bayes Approach to Statistics,`` in Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability, 1, 157-164.
    Stein, C. (1955). ""Inadmissibility of the Usual Estimators for the Mean of a Multivariate Normal Distribution,`` in Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability, 1, 197-206.
    描述: 碩士
    國立政治大學
    應用數學研究所
    94751002
    95
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0094751002
    資料類型: thesis
    顯示於類別:[應用數學系] 學位論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    100201.pdf73KbAdobe PDF2597檢視/開啟
    100202.pdf218KbAdobe PDF2686檢視/開啟
    100203.pdf33KbAdobe PDF2688檢視/開啟
    100204.pdf170KbAdobe PDF2688檢視/開啟
    100205.pdf378KbAdobe PDF2752檢視/開啟
    100206.pdf389KbAdobe PDF21008檢視/開啟
    100207.pdf461KbAdobe PDF2792檢視/開啟
    100208.pdf432KbAdobe PDF2747檢視/開啟
    100209.pdf439KbAdobe PDF2706檢視/開啟
    100210.pdf396KbAdobe PDF2836檢視/開啟
    100211.pdf348KbAdobe PDF2840檢視/開啟


    在政大典藏中所有的資料項目都受到原著作權保護.


    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 ©   - 回饋