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Symmetric Beta-Cauchy Distribution and Estimation of Parameters Using Order Statistics

机译:使用顺序统计量的对称Beta-Cauchy分布和参数估计

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In this work, we have considered a class of distributions called symmetric beta-Cauchy family of distributions (SBCD), and pointed out instances where SBCD appears as a good model to study the stochastic nature of the variable under investigation. We have derived the Best linear unbiased estimators (BLUE) based on order statistics of the location and scale parameters of SBCD for some given values of the shape parameter. Considering these BLUE's as kernels of degree m(≤5), we have further estimated the location and scale parameters of SBCD by U-statistics as seen developed recently by Thomas and Sreekumar for any sample of size n. The exact variances of the U-statistics have been obtained. The efficiency of the obtained estimators relative to some of the standard estimators has been also evaluated. An illustration describing the supremacy of U-statistics estimation method over the classical maximum likelihood method is also given.
机译:在这项工作中,我们考虑了一类称为对称β-柯西族分布(SBCD)的分布,并指出了SBCD似乎是研究被研究变量的随机性质的良好模型的实例。对于形状参数的某些给定值,我们基于SBCD的位置和比例参数的阶次统计量得出了最佳线性无偏估计量(BLUE)。将这些BLUE视为度数m(≤5)的核,我们通过U统计量进一步估计了SBCD的位置和尺度参数,这是Thomas和Sreekumar最近针对大小为n的任何样本开发的。已获得U统计量的确切方差。还评估了相对于一些标准估计量获得的估计量的效率。还给出了描述U统计估计方法相对于经典最大似然方法的至上性的说明。

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