English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62797/95867 (66%)
Visitors : 3746682      Online Users : 544
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU 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: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/19806


    Title: Generalized confidence intervals for the largest value of some functions of parameters under normality
    Authors: Chang, Y. P.;Huang, W. T.
    Contributors: 淡江大學經營決策學系
    Keywords: Bayesian confidence interval;Generalized confidence interval;Quantile;Signal-to-noise ratio
    Date: 2000-10
    Issue Date: 2013-08-08 14:47:40 (UTC+8)
    Publisher: Taipei: Academia Sinica * Institute of Statistical Science
    Abstract: This paper deals with generalized confidence intervals (GCIs) for the maximum value of functions of parameters of interest in the presence of nuisance parameters. For k(≥ 2) normal populations, we propose GCIs for, respectively, the largest mean, the largest quantile and the largest signal-to-noise ratio. For the case of the largest mean, it is shown that the proposed GCIs are better than those of Chen and Dudewicz (1973a, b). A new measure of efficiency is proposed and some Monte Carlo comparisons between the proposed method and the known method are performed. We also show that in several situations the GCIs are equivalent to Bayesian confidence intervals by employing improper prior distributions. Illustration is made to some real data.
    Relation: Statistica Sinica 10(4), pp.1369-1383
    Appears in Collections:[管理科學學系暨研究所] 期刊論文

    Files in This Item:

    File SizeFormat
    index.html0KbHTML240View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback