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  • 标题:Inference on P(X<Y) for Extreme Values
  • 本地全文:下载
  • 作者:Sudhansu S. Maiti ; Sudhir Murmu
  • 期刊名称:American Journal of Applied Mathematics and Statistics
  • 印刷版ISSN:2328-7306
  • 电子版ISSN:2328-7292
  • 出版年度:2014
  • 卷号:2
  • 期号:3
  • 页码:121-128
  • DOI:10.12691/ajams-2-3-6
  • 语种:English
  • 出版社:Science and Education Publishing
  • 摘要:The article considers the problem of , when X and Y belong to independently distributed two extreme value distributions. Maximum likelihood estimate of R has been found out and the estimates assuming different distributions have been compared for complete samples. Lower confidence limits of R have been found out by Delta method and bootstrap method. The Bayes estimate of R has also been calculated using MCMC approach.
  • 关键词:Bayes estimate; delta method; Lower Confidence Limit; Metropolis-Hastings algorithm
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