We consider a sequence of identical independently distributed random samples from an absolutely continuous probability measure in one dimension with unbounded density. We establish a new rate of convergence of the ∞ ∞ -Wasserstein distance between the empirical measure of the samples and the true distribution, which extends the previous convergence result by Trillos and Slepčev to the case that the true distribution has an unbounded density.
No takes yet. Share an insight, caveat, or question.
Liu et al. (2019) studied this question.
Synapse has enriched 3 closely related papers on similar clinical questions. Consider them for comparative context: