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Computational comparison of the general weighted moments estimators of the scale parameter of a Pareto distribution with a known shape parameter with other estimators based on a multiply type II-censored sample

机译:基于乘法II型删失样本的Pareto分布的比例参数(具有已知形状参数)的一般加权矩估计量与其他估计量的计算比较

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Wu et al. [Computational comparison for weighted moments estimators and BLUE of the scale parameter of a Pareto distribution with known shape parameter under type II multiply censored sample, Appl. Math. Comput. 181 (2006), pp. 1462-1470] proposed the weighted moments estimators (WMEs) of the scale parameter of a Pareto distribution with known shape parameter on a multiply type II-censored sample. They claimed that some WMEs are better than the best linear unbiased estimator (BLUE) based on the exact mean-squared error (MSE). In this paper, the general WME (GWME) is proposed and the computational comparison of the proposed estimator with the WMEs and BLUE is done on the basis of the exact MSE for given sample sizes and different censoring schemes. As a result, the GWME is performing better than the best estimator among 12 WMEs and BLUE for all cases. Therefore, GWME is recommended for use. At last, one example is given to demonstrate the proposed GWME.
机译:Wu等。 [加权矩估计量的计算比较和类型II乘删样本Appl下具有已知形状参数的Pareto分布的比例参数的BLUE。数学。计算181(2006),pp。1462-1470]提出了在倍数II删减样本上具有已知形状参数的帕累托分布的比例参数的加权矩估计量(WME)。他们声称,基于精确的均方误差(MSE),某些WME优于最佳线性无偏估计器(BLUE)。在本文中,提出了通用WME(GWME),并且在给定样本量和不同审查方案的情况下,在精确的MSE的基础上,将建议的估计量与WME和BLUE进行了计算比较。结果,在所有情况下,GWME的性能均优于12个WME和BLUE中的最佳估计器。因此,建议使用GWME。最后,给出了一个实例来说明所提出的GWME。

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