English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62567/95223 (66%)
Visitors : 2518599      Online Users : 315
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/987654321/123465

    Title: Bias-Corrected Maximum Likelihood Estimation for the Process Performance Index using Inverse Gaussian Distribution
    Authors: Tsai, Tzong-Ru;Xin, H;Fan, Ya-Yen;Lio, YL
    Keywords: Bias correction;bootstrap methods;Fisher information matrix;inverse Gaussian distribution;maximum likelihood estimation
    Date: 2022-08-04
    Issue Date: 2023-04-28 18:11:19 (UTC+8)
    Publisher: International Society of Science and Applied Technologies
    Abstract: An analytical bias-corrected maximum likelihood estimation procedure and a bootstrap bias-corrected maximum likelihood estimation procedure are proposed for the inverse Gaussian distribution (IGD) to obtain more reliable maximum likelihood estimates (MLEs) of the model parameters and the generalized process capability index (PCI) proposed by Maiti et al. (2010) when the sample size is small. An approximate confidence interval (ACI) of the generalized PCI is obtained for the IGD via using the delta method and the obtained reliable MLEs of the model parameters. Monte Carlo simulations were conducted to evaluate the performance of two proposed estimation methods. Simulation results show that two proposed bias-correction methods outperform the typical maximum likelihood estimation method when the sample size is small in terms of the relative bias and relative mean squared error. © 2022 International Society of Science and Applied Technologies
    Relation: 27th ISSAT International Conference on Reliability and Quality in Design, p.86-90
    Appears in Collections:[統計學系暨研究所] 會議論文

    Files in This Item:

    File SizeFormat

    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