淡江大學機構典藏:Item 987654321/124740
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 63246/95943 (66%)
Visitors : 4830866      Online Users : 141
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/987654321/124740


    Title: Estimation of stress-strength reliability for multicomponent system with a generalized inverted exponential distribution
    Authors: Wu, Shuo-jye
    Keywords: Bootstrap confidence interval;generalized inverted exponential distribution;generalized pivotal quantity;likelihood ratio test;maximum likelihood estimation;multicomponent stress-strength model
    Date: 2023-01-12
    Issue Date: 2023-11-13 12:05:29 (UTC+8)
    Abstract: Reliability analysis for a multicomponent stress-strength (MSS) model is discussed in this paper. When strength and stress variables follow generalized inverted exponential distributions (GIEDs) with common scale parameters, maximum likelihood estimate of MSS reliability is established along with associated existence and uniqueness, and approximate confidence interval is also obtained in consequence. Additionally, alternative generalized estimates are proposed for MSS reliability based on constructed pivotal quantities, and associated Monte-Carlo sampling is provided for computation. Further, classical and generalized estimates are also established under unequal strength and stress parameter case. For comparison, bootstrap confidence intervals are also provided under different cases. To compare the equivalence of the strength and stress parameters, likelihood ratio testing is presented as a complement. Finally, extensive simulation studies are carried out to assess the performance of the proposed methods, and a real data example is presented for application. The numerical results indicate that the proposed generalized methods perform better than conventional likelihood results.
    Relation: Stochastic Models 39(4), p.715-740
    DOI: 10.1080/15326349.2022.2162545
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML44View/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