28 pagesWe are interested in the approximation in Wasserstein distance with index $\rho\ge 1$ of a probability measure $\mu$ on the real line with finite moment of order $\rho$ by the empirical measure of $N$ deterministic points. The minimal error converges to $0$ as $N\to+\infty$ and we try to characterize the order associated with this convergence. Apart when $\mu$ is a Dirac mass and the error vanishes, the order is not larger than $1$. We give a necessary condition and a sufficient condition for the order to be equal to this threshold $1$ in terms of the density of the absolutely continuous with respect to the Lebesgue measure part of $\mu$. We also check that for the order to lie in the interval $\left(1/\rho,1\right)$, the support of...
AbstractAn upper bound is given for the mean square Wasserstein distance between the empirical measu...
Let M be a d-dimensional connected compact Riemannian manifold with boundary ∂M, let V∈C2(M) such th...
We estimate the Wasserstein type distance between two continuous distributions F and G on R such tha...
28 pagesInternational audienceWe are interested in the approximation in Wasserstein distance with in...
We provide some non asymptotic bounds, with explicit constants, that measure the rate of convergence...
The Wasserstein distance between two probability measures on a metric spaceis a measure of closeness...
We provide some non-asymptotic bounds, with explicit constants, that measure the rate of convergence...
An upper bound is given for the mean square Wasserstein distance between the empirical measure of a ...
We consider the problem of approximating a probability measure defined on a metric space b...
We establish some deviation inequalities, moment bounds and almost sure results for the Wasserstein ...
This paper is focused on the statistical analysis of probability measures $\bnu_{1},\ldots,\bnu_{n}$...
Abstract. Let µN be the empirical measure associated to a N-sample of a given probability distributi...
International audienceThis paper deals with the estimation of a probability measure on the real line...
The Wasserstein distance is an attractive tool for data analysis but statistical inference is hinder...
In this work, we provide non-asymptotic bounds for the average speed of convergence of the empirical...
AbstractAn upper bound is given for the mean square Wasserstein distance between the empirical measu...
Let M be a d-dimensional connected compact Riemannian manifold with boundary ∂M, let V∈C2(M) such th...
We estimate the Wasserstein type distance between two continuous distributions F and G on R such tha...
28 pagesInternational audienceWe are interested in the approximation in Wasserstein distance with in...
We provide some non asymptotic bounds, with explicit constants, that measure the rate of convergence...
The Wasserstein distance between two probability measures on a metric spaceis a measure of closeness...
We provide some non-asymptotic bounds, with explicit constants, that measure the rate of convergence...
An upper bound is given for the mean square Wasserstein distance between the empirical measure of a ...
We consider the problem of approximating a probability measure defined on a metric space b...
We establish some deviation inequalities, moment bounds and almost sure results for the Wasserstein ...
This paper is focused on the statistical analysis of probability measures $\bnu_{1},\ldots,\bnu_{n}$...
Abstract. Let µN be the empirical measure associated to a N-sample of a given probability distributi...
International audienceThis paper deals with the estimation of a probability measure on the real line...
The Wasserstein distance is an attractive tool for data analysis but statistical inference is hinder...
In this work, we provide non-asymptotic bounds for the average speed of convergence of the empirical...
AbstractAn upper bound is given for the mean square Wasserstein distance between the empirical measu...
Let M be a d-dimensional connected compact Riemannian manifold with boundary ∂M, let V∈C2(M) such th...
We estimate the Wasserstein type distance between two continuous distributions F and G on R such tha...