methodology with non-Euclidean data sets. Specifically, it provides the basis and rationale for statistics in Wasserstein space …, where the metric on probability measures is taken as a Wasserstein metric arising from optimal transport theory. Design …/methodology/approach - The authors spell out the basis and rationale for using Wasserstein metrics on the data space of (random) probability …

derive a bound for the Wasserstein distance of the finite-sample distribution of the estimator of the autocovariance and … Wasserstein distances obtained via simulation. …