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Exact rate of convergence of the mean Wasserstein distance between the empirical and true Gaussian distribution
Published 27 Jan 2020 in math.PR, math.ST, and stat.TH | (2001.09817v1)
Abstract: 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.
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