Analysis of statistical equilibrium models of geostrophic turbulence.
Analytically normed spaces.
Annealed deviations of random walk in random scenery
Annealed Lyapounov exponents and large deviations in a poissonian potential. II
Annealed Lyapounov exponents and large deviations in a poissonian potential. I
Anomalous heat-kernel decay for random walk among bounded random conductances
We consider the nearest-neighbor simple random walk on ℤd, d≥2, driven by a field of bounded random conductances ωxy∈[0, 1]. The conductance law is i.i.d. subject to the condition that the probability of ωxy>0 exceeds the threshold for bond percolation on ℤd. For environments in which the origin is connected to infinity by bonds with positive conductances, we study the decay of the 2n-step return probability . We prove that is bounded by a random constant timesn−d/2 in d=2, 3, while it...
Another look at the moment method for large dimensional random matrices.
Antisymmetric functionals of reversible Markov processes
Applications of sharp large deviations estimates to optimal cooling schedules
Applications radonifiantes dans l'espace des séries convergentes. II. Les résultats
Applications radonifiantes dans l'espace des séries convergentes. I. Le théorème de Menchov
Approximation at first and second order of -order integrals of the fractional Brownian motion and of certain semimartingales.
Approximation by Poisson law
We present here the results of the investigation on approximation by the Poisson law of distributions of sums of random variables in the scheme of series. We give the results pertaining to the behaviour of large deviation probabilities and asymptotic expansions, to the method of cumulants, with the aid of which our results have been obtained.
Approximation des trajectoires et temps local des diffusions
Approximation in law to the d-parameter fractional Brownian sheet based on the functional invariance principle.
We show a result of approximation in law of the d-parameter fractional Brownian sheet in the space of the continuous functions on [0,T]d. The construction of these approximations is based on the functional invariance principle.
Approximation of bivariate Markov chains by one-dimensional diffusion processes
The paper deals with several questions of the diffusion approximation. The goal of this paper is to create the general method of reducting the dimension of the model with the aid of the diffusion approximation. Especially, two dimensional random variables are approximated by one-dimensional diffusion process by replacing one of its coordinates by a certain characteristic, e.g. by its stationary expectation. The suggested method is used for several different systems. For instance, the method is applicable...
Approximation of predictable characteristics of processes with filtrations
Approximations for the maximum of stochastic processes with drift
If a stochastic process can be approximated with a Wiener process with positive drift, then its maximum also can be approximated with a Wiener process with positive drift.
Approximations of the brownian rough path with applications to stochastic analysis
Approximative solutions of stochastic optimization problems
The aim of this paper is to present some ideas how to relax the notion of the optimal solution of the stochastic optimization problem. In the deterministic case, -minimal solutions and level-minimal solutions are considered as desired relaxations. We call them approximative solutions and we introduce some possibilities how to combine them with randomness. Relations among random versions of approximative solutions and their consistency are presented in this paper. No measurability is assumed, therefore,...