  In this paper numerical methods of computing distances between two Radon
measures on R are discussed. Efficient algorithms for Wasserstein-type metrics
are provided. In particular, we propose a novel algorithm to compute the flat
metric (bounded Lipschitz distance) with a computational cost O(nlogn). The
flat distance has recently proven to be adequate for the Escalator Boxcar Train
(EBT) method for solving transport equations with growth terms. Therefore,
finding efficient numerical algorithms to compute the flat distance between two
measures is important for finding the residual error and validating empirical
convergence of different methods.
