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1 vote

Lipschitz-type inequalities for Markov kernels

Assuming that your distance is convex, the question reduces just to the case when both $\mu$ and $\nu$ are delta measures, and amounts then to the inequality $$\tag {$\star$} d(\delta_x,\delta_y) \le …
R W's user avatar
  • 17k
6 votes
Accepted

Wasserstein distance in R^d from one dimensional marginals

There is a result which contains an answer to your question in a somewhat different form. Instead of the transportation metric it uses another metric which metrizes the weak topology in the space of m …
Martin Sleziak's user avatar
10 votes
Accepted

Upper bound total variation by Wasserstein distance for continuous distance

No. One should realize that the transportation and the total variation distances metrize two quite different topologies. Even if the measures are equivalent (i.e., absolutely continuous with respect t …
R W's user avatar
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14 votes
Accepted

Metrization of weak convergence of signed measures

Of course, there are many ways of metrizing the weak topology on $\mathcal M(\Omega)$ by using various tools of functional analysis. However, as it has already been pointed out by Dan, the most natura …
R W's user avatar
  • 17k