It is well known that central order statistics exhibit a central limit behavior and converge to a Gaussian distribution as the sample size grows. This paper strengthens this known result by establishing an entropic version of the CLT that ensures a stronger mode of convergence using the relative entropy. In particular, an order $O(1/\sqrt{n})$ rate of convergence is established under mild conditions on the parent distribution of the sample generating the order statistics. To prove this result, ancillary results on order statistics are derived, which might be of independent interest.
翻译:众所周知,中央秩序统计呈现出一种核心极限行为,随着抽样规模的扩大,与高斯的分布情况趋于一致。本文通过建立CLT的通俗版加强了这一已知结果,该版本确保使用相对的对流体实现更强大的趋同模式。特别是,在生成定序统计数据的样本的母体分布的温和条件下确定了美元(1/\sqrt{n})汇合率。为了证明这一结果,可以得出关于定序统计数据的辅助结果,这可能具有独立的兴趣。