English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62830/95882 (66%)
Visitors : 4037907      Online Users : 559
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/987654321/110426


    Title: Bayesian estimation and prediction based on lognormal record values
    Authors: Singh, Sukhdev;Tripathi, Yogesh Mani;Wu, Shuo-Jye
    Keywords: Asymptotic confidence interval;Bayesian estimation;equal-tail interval;highest posterior density interval;inter-record times;prediction
    Date: 2017-03
    Issue Date: 2017-06-28 02:10:21 (UTC+8)
    Publisher: Routledge
    Abstract: In this paper we consider the problems of estimation and prediction when observed data from a lognormal distribution are based on lower record values and lower record values with inter-record times. We compute maximum likelihood estimates and asymptotic confidence intervals for model parameters. We also obtain Bayes estimates and the highest posterior density (HPD) intervals using noninformative and informative priors under square error and LINEX loss functions. Furthermore, for the problem of Bayesian prediction under one-sample and two-sample framework, we obtain predictive estimates and the associated predictive equal-tail and HPD intervals. Finally for illustration purpose a real data set is analyzed and simulation study is conducted to compare the methods of estimation and prediction.
    Relation: Journal of Applied Statistics 44(5), p. 916-940
    DOI: 10.1080/02664763.2016.1189520
    Appears in Collections:[統計學系暨研究所] 期刊論文

    Files in This Item:

    File Description SizeFormat
    Bayesian estimation and prediction based on lognormal record values.pdf2098KbAdobe PDF1View/Open
    index.html0KbHTML167View/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