Sample path large deviations principles for Poisson shot noise processes, and applications.
Scaling limit of the prudent walk.
Scaling limit of the random walk among random traps on ℤd
Attributing a positive value τx to each x∈ℤd, we investigate a nearest-neighbour random walk which is reversible for the measure with weights (τx), often known as “Bouchaud’s trap model.” We assume that these weights are independent, identically distributed and non-integrable random variables (with polynomial tail), and that d≥5. We obtain the quenched subdiffusive scaling limit of the model, the limit being the fractional kinetics process. We begin our proof by expressing the random walk as the...
Scaling of a random walk on a supercritical contact process
We prove a strong law of large numbers for a one-dimensional random walk in a dynamic random environment given by a supercritical contact process in equilibrium. The proof uses a coupling argument based on the observation that the random walk eventually gets trapped inside the union of space–time cones contained in the infection clusters generated by single infections. In the case where the local drifts of the random walk are smaller than the speed at which infection clusters grow, the random walk...
Self Diffusion of a tagged particle in equilibrium for asymmetric mean zero random walk with simple exclusion
Semi-martingales and rough paths theory.
Singleton independence
Motivated by the central limit problem for algebraic probability spaces arising from the Haagerup states on the free group with countably infinite generators, we introduce a new notion of statistical independence in terms of inequalities rather than of usual algebraic identities. In the case of the Haagerup states the role of the Gaussian law is played by the Ullman distribution. The limit process is realized explicitly on the finite temperature Boltzmannian Fock space. Furthermore, a functional...
Small positive values for supercritical branching processes in random environment
Branching Processes in Random Environment (BPREs) are the generalization of Galton–Watson processes where in each generation the reproduction law is picked randomly in an i.i.d. manner. In the supercritical case, the process survives with positive probability and then almost surely grows geometrically. This paper focuses on rare events when the process takes positive but small values for large times. We describe the asymptotic behavior of , as . More precisely, we characterize the exponential...
Some almost sure results for unbounded functions of intermittent maps and their associated Markov chains
We consider a large class of piecewise expanding maps T of [0, 1] with a neutral fixed point, and their associated Markov chains Yi whose transition kernel is the Perron–Frobenius operator of T with respect to the absolutely continuous invariant probability measure. We give a large class of unbounded functions f for which the partial sums of f○Ti satisfy both a central limit theorem and a bounded law of the iterated logarithm. For the same class, we prove that the partial sums of f(Yi) satisfy a...
Some applications of probability generating function based methods to statistical estimation
After recalling previous work on probability generating functions for real valued random variables we extend to these random variables uniform laws of large numbers and functional limit theorem for the empirical probability generating function. We present an application to the study of continuous laws, namely, estimation of parameters of Gaussian, gamma and uniform laws by means of a minimum contrast estimator that uses the empirical probability generating function of the sample. We test the procedure...
Some asymptotic properties of the hybrids of empirical and partial-sum processes.
Some exact rates in the functional law of the iterated logarithm
Some families of increasing planar maps.
Some Invariance Principles for Stochastic Processes and Their Inverse and Supremum Processes.
Stein’s method in high dimensions with applications
Let be a three times partially differentiable function on , let be a collection of real-valued random variables and let be a multivariate Gaussian vector. In this article, we develop Stein’s method to give error bounds on the difference in cases where the coordinates of are not necessarily independent, focusing on the high dimensional case . In order to express the dependency structure we use Stein couplings, which allows for a broad range of applications, such as classic occupancy,...
Stochastic Random Walk Summability.
Strong approximation for mixing sequences with infinite variance.
Strong limit theorems for a simple random walk on the 2-dimensional comb.
Sur la convergence des semimartingales vers un processus à accroissements indépendants
Sur la persistance du processus de Dawson-Watanabe stable. L'interversion de la limite en temps et de la renormalisation