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Random Weighting Empirical Distribution Function and its Applications to Goodness-of-Fit Testing

机译:随机加权经验分布函数及其在拟合优度检验中的应用

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In this article, a randomized estimator of the empirical distribution function (EDF) called random weighting empirical distribution function (RWEDF) is introduced, one special case of which is just equivalent to the Bayesian bootstrap. The consistency of the RWEDF is established under certain conditions. By substituting this new EDF for the classical EDF, we obtain new versions of some EDF test statistics for goodness-of-fit. The simulation results show that the new tests are more powerful than the corresponding tests based on the classical EDF under some cases.
机译:在本文中,介绍了一种称为经验加权分布函数(RWEDF)的随机分布的经验分布函数(EDF)估计量,其中一种特殊情况与贝叶斯自举等效。 RWEDF的一致性是在某些条件下建立的。通过用新的EDF代替经典的EDF,我们获得了一些新的EDF测试统计数据,以证明拟合优度。仿真结果表明,在某些情况下,新测试比基于经典EDF的相应测试功能更强大。

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