Limit laws of the empirical Wasserstein distance: Gaussian distributions

From MaRDI portal
Publication:311810

DOI10.1016/j.jmva.2016.06.005zbMath1351.62064arXiv1507.04090OpenAlexW2244432928MaRDI QIDQ311810

Thomas Rippl, Axel Munk, Anja Sturm

Publication date: 13 September 2016

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1507.04090




Related Items (25)

Optimal-order bounds on the rate of convergence to normality in the multivariate delta methodOptimal Transport for Parameter Identification of Chaotic Dynamics via Invariant MeasuresDistributionally-robust machine learning using locally differentially-private dataConvergence and finite sample approximations of entropic regularized Wasserstein distances in Gaussian and RKHS settingsMinimax confidence intervals for the sliced Wasserstein distanceSome multivariate goodness of fit tests based on data depthA central limit theorem for Wasserstein type distances between two distinct univariate distributionsGaussian approximation for penalized Wasserstein barycentersDensity estimation of multivariate samples using Wasserstein distanceInference for Empirical Wasserstein Distances on Finite SpacesWide consensus aggregation in the Wasserstein space. Application to location-scatter familiesSemi-discrete optimal transport: a solution procedure for the unsquared Euclidean distance caseElements of Statistical Inference in 2-Wasserstein SpaceFréchet means and Procrustes analysis in Wasserstein spaceStatistical inference for Bures-Wasserstein barycentersHybrid Wasserstein distance and fast distribution clusteringCentral limit theorems for entropy-regularized optimal transport on finite spaces and statistical applicationsEmpirical optimal transport on countable metric spaces: distributional limits and statistical applicationsAsymptotic distribution and convergence rates of stochastic algorithms for entropic optimal transportation between probability measuresOptimal uncertainty size in distributionally robust inverse covariance estimationMultivariate goodness-of-fit tests based on Wasserstein distanceProcrustes metrics on covariance operators and optimal transportation of Gaussian processesMeasuring dependence between random vectors via optimal transportEmpirical Regularized Optimal Transport: Statistical Theory and ApplicationsDistributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator



Cites Work


This page was built for publication: Limit laws of the empirical Wasserstein distance: Gaussian distributions