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  • 标题:One-sequence and two-sequence prediction for future Weibull records
  • 本地全文:下载
  • 作者:Omar M. Bdair ; Mohammad Z. Raqab
  • 期刊名称:Journal of Statistical Theory and Applications (JSTA)
  • 电子版ISSN:1538-7887
  • 出版年度:2016
  • 卷号:15
  • 期号:4
  • 页码:347-368
  • DOI:10.2991/jsta.2016.15.4.3
  • 语种:English
  • 出版社:Atlantis Press
  • 摘要:Based on record data, prediction of the future records from the two-parameter Weibull distribution is studied. First we consider the sampling based procedure to compute the Bayes estimates and also to construct symmetric credible intervals. Secondly, we consider one-sequence and two-sequence Bayes prediction of the future records based on some observed records. The Monte Carlo algorithms are used to compute simulation consistent predictors and prediction intervals for future unobserved records. A numerical simulation study is conducted to compare the different methods and a real data set involving the annual rainfall recorded at Los Angeles Civic Center during 132 years is analyzed to illustrate the procedures developed here.
  • 关键词:Weibull distribution; record values; Bayes estimation; Bayes prediction; Monte Carlo samples.
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