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  • 标题:Bayesian and Frequentist Prediction Using Progressive Type-II Censored with Binomial Removals
  • 本地全文:下载
  • 作者:Ahmed A. Soliman ; Ahmed H. Abd Ellah ; Nasser A. Abou-Elheggag
  • 期刊名称:Intelligent Information Management
  • 印刷版ISSN:2150-8194
  • 电子版ISSN:2150-8208
  • 出版年度:2013
  • 卷号:5
  • 期号:5
  • 页码:162-170
  • DOI:10.4236/iim.2013.55017
  • 出版社:Scientific Research Publishing
  • 摘要:In this article, we study the problem of predicting future records and order statistics (two-sample prediction) based on progressive type-II censored with random removals, where the number of units removed at each failure time has a discrete binomial distribution. We use the Bayes procedure to derive both point and interval bounds prediction. Bayesian point prediction under symmetric and symmetric loss functions is discussed. The maximum likelihood (ML) prediction intervals using “plug-in” procedure for future records and order statistics are derived. An example is discussed to illustrate the application of the results under this censoring scheme.
  • 关键词:Bayesian Prediction; Burr-X Model; Progressive Censoring; Random Removals
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