English  |  正體中文  |  简体中文  |  Items with full text/Total items : 69937/69937 (100%)
Visitors : 23028006      Online Users : 571
RC Version 7.0 © 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

    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/62883

    Title: 分析相關性資料的普世強韌複合概似函數;Universal Robust Composite Likelihood for General Correlated Data
    Authors: 鄒宗山
    Contributors: 國立中央大學統計研究所
    Keywords: 數學;統計學
    Date: 2013-12-01
    Issue Date: 2014-03-17 14:08:46 (UTC+8)
    Publisher: 行政院國家科學委員會
    Abstract: 研究期間:10208~10307;The method of composite likelihood was introduced by Lindsay (1988) for correlated data. This parametric approach provides consistent regression parameter estimates and can be used to create likelihood ratio test. However, some drawbacks are notable. For example, the large sample composite likelihood ratio test doesn't have the familiar standard chi-square distribution, and no legitimate likelihood function is available by the composite likelihood when model assumption fails. The multivariate negative binomial distribution has been shown to be a superb simple working model for analyzing correlated data. One can operate on the robust negative binomial likelihood function to acquire legitimate likelihood-based inferential tools, such as the likelihood ratio and the score tests and goodness of fit test. There are two goals this research proposal wishes to accomplish. One is to establish composite likelihood using the multivariate negative binomial distribution as the core model. Secondly, we will contrast the normal-based composite likelihood and the negative binomial-based composite likelihood in terms of 1) legitimacy 2) efficiency and 3) simplicity, when the score model assumption fails. According to the plentiful experiences on robust likelihood, we are confident that the latter will be a better choice for correlated data under model misspecifications.
    Relation: 財團法人國家實驗研究院科技政策研究與資訊中心
    Appears in Collections:[統計研究所] 研究計畫

    Files in This Item:

    File Description SizeFormat

    All items in NCUIR are protected by copyright, with all rights reserved.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback  - 隱私權政策聲明