English  |  正體中文  |  简体中文  |  Items with full text/Total items : 68069/68069 (100%)
Visitors : 23222164      Online Users : 145
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/987654321/80940

    Title: Estimation in Copula-Based Markov Models under Weibull Distributions
    Authors: 葉俞佑;Yeh, Yu-Yu
    Contributors: 統計研究所
    Keywords: 馬可夫模型;觀察Fisher信息矩陣;韋伯分佈;指數分配;Markov model;Survival-Gumbel copula;observed Fisher information matrix;Weibull distribution;exponential distribution
    Date: 2019-08-19
    Issue Date: 2019-09-03 15:18:15 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 我們提出了基於 copula 的馬可夫模型的估計問題,因為在實踐中,連續數據通常具有相關性結構。在這個項目中,我們研究了 survival-Gumbel copula,其邊際分佈是韋伯分佈。我們獲得似然函數以及最大似然估計量。另外,為了解決區間估計,我們用三個觀察 Fisher 信息矩陣估計標準誤差。在模擬研究中,通過覆蓋概率比較三種方法哪一種更適合所提出的模型。最後,在實證研究中,分析了從 2005/1/1 到 2017/1/1 的每日收盤價 VIX 及在西班牙醫院開展手術的結直腸癌患者進行說明。特別是,我們研究了 VIX 數據的兩個邊際分佈,即韋伯分佈和指數分佈。;We propose the estimation problem for a copula-based Markov model since in practice, serially data often has the dependent structure. In this project, we study the survival-Gumbel copula with the marginal distribution being the Weibull distribution. The likelihood function and the maximum likelihood estimators (MLEs) are obtained. In addition, in order to solve the interval estimation, we estimate the standard errors (SEs) with the three observed Fisher information matrices. The comparison of the three methods for investigating which one is more suitable for the proposed model in terms of the coverage probability through the simulation study. Finally, in the empirical study, the daily close VIX from 2005/1/1 to 2017/1/1 and the patients with colorectal cancer who have operations in a hospital in Spain are analyzed for illustration. In particular, we study two marginal distributions for the data, which are the Weibull distribution and the exponential distribution.
    Appears in Collections:[統計研究所] 博碩士論文

    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