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Improved confidence regions for a mean vector under general conditions

机译:一般条件下均值向量的改进置信区域

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摘要

In this paper, we propose two different confidence regions for a mean vector under general conditions when the population of interest is nonnormal and the sample size is moderate. It is shown that both confidence regions will improve the accuracy of the approximation in the sense that the coverage error is of order o(n-1). Monte Carlo examples are demonstrated to show the performance with comparison to the classical methods.
机译:在本文中,当感兴趣的总体非正常且样本大小适中时,我们为一般条件下的均值向量提出了两个不同的置信区域。从覆盖误差约为o(n-1)的意义上看,两个置信区域都将提高近似精度。演示了蒙特卡洛示例,以显示与传统方法相比的性能。

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