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Exact rate of convergence of the expected $W_{2}$ distance between the empirical and true Gaussian distribution

机译:预期$ W_ {2}在经验和真正的高斯分布之间的预期$ W_ {2}的确切汇率

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摘要

We study the Wasserstein distance $W_{2}$ for Gaussian samples. We establish the exact rate of convergence $sqrt{log log n/n} $ of the expected value of the $W_{2}$ distance between the empirical and true $c.d.f.$’s for the normal distribution. We also show that the rate of weak convergence is unexpectedly $1/sqrt{n} $ in the case of two correlated Gaussian samples.
机译:我们研究高斯样本的Wassersein距离$ w_ {2} $。我们建立了在经验和真实$ c.f之间的$ w_ {2} $距离的预期值的确切融合率$ sqrt { log log n / n} $。$'s正常分布。我们还表明,在两个相关的高斯样本的情况下,弱收敛速率意外地是1 / SQRT {n} $。

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