Calcul des probabilités - Théorème des grands écarts et théorème de la limite centrale pour certains produits de matrices aléatoires
Chernoff and Berry–Esséen inequalities for Markov processes
In this paper, we develop bounds on the distribution function of the empirical mean for general ergodic Markov processes having a spectral gap. Our approach is based on the perturbation theory for linear operators, following the technique introduced by Gillman.
Chernoff and Berry–Esséen inequalities for Markov processes
In this paper, we develop bounds on the distribution function of the empirical mean for general ergodic Markov processes having a spectral gap. Our approach is based on the perturbation theory for linear operators, following the technique introduced by Gillman.
Coboundaries in
Comparison theorems for small deviations of random series.
Comparisons between tail probabilities of sums of independent symmetric random variables
Concentration of the Brownian bridge on Cartan-Hadamard manifolds with pinched negative sectional curvature
We study the rate of concentration of a Brownian bridge in time one around the corresponding geodesical segment on a Cartan-Hadamard manifold with pinched negative sectional curvature, when the distance between the two extremities tends to infinity. This improves on previous results by A. Eberle, and one of us . Along the way, we derive a new asymptotic estimate for the logarithmic derivative of the heat kernel on such manifolds, in bounded time and with one space parameter...
Concentration of the spectral measure for large matrices.
Concentration of the spectral measure of large Wishart matrices with dependent entries.
Conditional principles for random weighted measures
In this paper, we prove a conditional principle of Gibbs type for random weighted measures of the form , being a sequence of i.i.d. real random variables. Our work extends the preceding results of Gamboa and Gassiat (1997), in allowing to consider thin constraints. Transportation-like ideas are used in the proof.
Conditional principles for random weighted measures
In this paper, we prove a conditional principle of Gibbs type for random weighted measures of the form , ((Zi)i being a sequence of i.i.d. real random variables. Our work extends the preceding results of Gamboa and Gassiat (1997), in allowing to consider thin constraints. Transportation-like ideas are used in the proof.
Convex concentration inequalities and forward-backward stochastic calculus.
Cramer Type Large Deviations for Studentized U-Statistics.
Cramér type moderate deviations for Studentized U-statistics
Let Tn be a Studentized U-statistic. It is proved that a Cramér type moderate deviation P(Tn ≥ x)/(1 − Φ(x)) → 1 holds uniformly in x ∈ [0, o(n1/6)) when the kernel satisfies some regular conditions.
Cramér type moderate deviations for Studentized U-statistics******
Let Tn be a Studentized U-statistic. It is proved that a Cramér type moderate deviation P(Tn ≥ x)/(1 − Φ(x)) → 1 holds uniformly in x∈ [0, o(n1/6)) when the kernel satisfies some regular conditions.
Cram'er type moderate deviations for the maximum of self-normalized sums.