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New Bayes Estimator of Parameter Weibull Distribution

机译:参数威布尔分布的新贝叶斯估计

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In this paper the Jeffery prior information and the extension of Jeffery prior information for estimating the parameter Weibull distribution is presented. Through simulation study the performance of this estimator was compared to the standard Bayes with Jeffery prior information with respect to the mean square error (MSE) and mean percentage error (MPE). In the results, The new estimator with extension of Jeffery prior information is the best estimator for Weibull Distribution, when compared it with standard Bayes with Jeffery prior information. Also depending on MSE and MPE, the is the best survival function for Weibull distribution when compared it with survival function based on posterior distribution. We can easily conclude that MSE and MPE of Bayes estimators decrease with an increased of sample size.
机译:本文提出了Jeffery先验信息和Jeffery先验信息的扩展,用于估计参数Weibull分布。通过仿真研究,将该估计器的性能与具有Jeffery先验信息的标准Bayes的均方误差(MSE)和均值百分比误差(MPE)进行了比较。结果是,与具有Jeffery先验信息的标准Bayes进行比较时,具有Jeffery先验信息的扩展的新估计量是Weibull分布的最佳估计量。同样取决于MSE和MPE,与基于后验分布的生存函数相比,Wis是威布尔分布的最佳生存函数。我们可以轻松得出结论,贝叶斯估计量的MSE和MPE随着样本量的增加而降低。

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