Grandes déviations pour les mesures de Gibbs lorsque la température tend vers zéro
Grandes déviations pour un système hydrodynamique asymétrique de particules indépendantes
Grandes déviations spatiales pour un système gradient stochastique infini-dimensionnel
Grandi deviazioni e importance sampling per processi di Poisson Markov modulati
Identification of the rate function for large deviations of an irreducible Markov chain.
Insensitivity to negative dependence of the asymptotic behavior of precise large deviations.
Integro-local and integral limit theorems on the large deviations of sums of random vectors: Regular distributions.
Integro-local and integral theorems for sums of random variables with semiexponential distributions.
Interface for one-dimensional random Kac potentials
Intermittency on catalysts: symmetric exclusion.
Internal DLA in a random environment
Intersecting random translates of invariant Cantor sets.
Karhunen-Loève expansions of α-Wiener bridges
We study Karhunen-Loève expansions of the process(X t(α))t∈[0,T) given by the stochastic differential equation , with the initial condition X 0(α) = 0, where α > 0, T ∈ (0, ∞), and (B t)t≥0 is a standard Wiener process. This process is called an α-Wiener bridge or a scaled Brownian bridge, and in the special case of α = 1 the usual Wiener bridge. We present weighted and unweighted Karhunen-Loève expansions of X (α). As applications, we calculate the Laplace transform and the distribution function...
La convergence en probabilité et la convergence presque sûre de certaines suites de variables aléatoires dépendantes
Large and moderate deviations for Hotelling's -statistic.
Large and moderate deviations for moving average processes
Large and moderate deviations for the local time of a recurrent Markov chain on
Large and Moderate Deviations Principles for Recursive Kernel Estimator of a Multivariate Density and its Partial Derivatives
2000 Mathematics Subject Classification: 62G07, 60F10.In this paper we prove large and moderate deviations principles for the recursive kernel estimator of a probability density function and its partial derivatives. Unlike the density estimator, the derivatives estimators exhibit a quadratic behaviour not only for the moderate deviations scale but also for the large deviations one. We provide results both for the pointwise and the uniform deviations.
Large deviation estimate of transition densities for jump processes
Large deviation principle and inviscid shell models.