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Statement of Retraction

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摘要

The uniform minimum variance unbiased (UMVU), maximum likelihood (ML), moment (MM), quantile (MQ) and least squares (LS) estimations of the probability density function (pdf), cumulative distribution function (CDF) and rth moment are derived for the exponentiated Pareto distribution in the presence of outliers. It has been shown that MLE is better than UMVUE and UMVUE is better than the others. Also, UMVU and ML estimators of the rth moment are more efficient than its MQ and LS estimators. Further, it has been shown that for high values of sample size, UMVUE of the rth moment is better than MLE. Finally, an example with actual data from an insurance company has been given.
机译:概率密度函数(pdf),累积分布函数(CDF)和rth矩的统一最小方差无偏(UMVU),最大似然(ML),矩(MM),分位数(MQ)和最小二乘(LS)估计为在存在异常值的情况下针对指数Pareto分布得出。已经表明,MLE比UMVUE更好,而UMVUE则优于其他。同样,第一个矩的UMVU和ML估计器比其MQ和LS估计器更有效。此外,已经表明,对于高样本量值,第一个矩的UMVUE优于MLE。最后,给出了一个来自保险公司的实际数据的例子。

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  • 来源
    《Statistics》 |2011年第3期|p.121-122|共2页
  • 作者单位

    Department of Statistics, Ordered and Spatial Data Center of Excellence, Ferdowsi University of Mashhad, Mashhad, Iran;

    Department of Statistics, Ordered and Spatial Data Center of Excellence, Ferdowsi University of Mashhad, Mashhad, Iran;

  • 收录信息 美国《科学引文索引》(SCI);
  • 原文格式 PDF
  • 正文语种 eng
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