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  • 标题:Confidence Intervals for the Scaled Half-Logistic Distribution under Progressive Type-II Censoring
  • 本地全文:下载
  • 作者:Potdar, Kiran Ganpati ; Shirke, D. T
  • 期刊名称:Journal of Modern Applied Statistical Methods
  • 出版年度:2017
  • 卷号:16
  • 期号:1
  • 页码:19
  • 出版社:Wayne State University
  • 摘要:Confidence interval construction for the scale parameter of the half-logistic distribution is considered using four different methods. The first two are based on the asymptotic distribution of the maximum likelihood estimator (MLE) and log-transformed MLE. The last two are based on pivotal quantity and generalized pivotal quantity, respectively. The MLE for the scale parameter is obtained using the expectation-maximization (EM) algorithm. Performances are compared with the confidence intervals proposed by Balakrishnan and Asgharzadeh via coverage probabilities, length, and coverage-to-length ratio. Simulation results support the efficacy of the proposed approach.
  • 关键词:Progressively Type-II censoring; EM algorithm; MLE; pivotal quantity; confidence interval; generalized confidence interval; coverage probability; coverage to length ratio; half-logistic distribution.
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