A Weighted Approximation Approach to the Study of the Empirical Wasserstein Distance

DOI10.1007/978-3-319-40519-3_6zbMath1355.60040OpenAlexW2523297450MaRDI QIDQ2954042

David M. Mason

Publication date: 11 January 2017

Published in: High Dimensional Probability VII (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-40519-3_6

zbMATH Keywords

empirical processweighted approximationWasserstein distance

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Approximations to statistical distributions (nonasymptotic) (62E17) Functional limit theorems; invariance principles (60F17)

Related Items (1)

Empirical optimal transport on countable metric spaces: distributional limits and statistical applications

Cites Work

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• Weighted empirical and quantile processes
• A refinement of the KMT inequality for the uniform empirical process
• The asymptotic distribution of trimmed sums
• A probabilistic approach to the asymptotic distribution of sums of independent, identically distributed random variables
• The Brunn-Minkowski inequality in Gauss space
• Central limit theorems for the Wasserstein distance between the empirical and the true distributions
• An approximation of partial sums of independent RV'-s, and the sample DF. I
• Nonparametric Validation of Similar Distributions and Assessment of Goodness of Fit
• Inequalities for quantile functions with a uniform studentized clt that includes trimming
• An exponential inequality for a weighted approximation to the uniform empirical process with applications
• New concentration inequalities in product spaces

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