Caractérisation d'une solution optimale au problème de Monge-Kantorovitch
Caractéristiques locales des semi-martingales et changements de probabilités
Caracterización axiomática para la varianza.
En el artículo ([7]), M. Martín propone dos caracterizaciones axiomáticas para la varianza sugiriendo la posibilidad de caracterizarla de forma más intuitiva como una medida de incertidumbre que tenga en cuenta el soporte de la probabilidad, además del valor de ésta.El presente trabajo está dedicado a establecer una caracterización en tal sentido, siguiendo la línea de la axiomática de D. K. Faddeyew para la entropía de Shannon y de la axiomática propuesta en ([3]) para la medida definida en ([2]).Queremos...
Caracterización geométrica de la independencia en un espacio gaussiano.
Carthaginian enlargement of filtrations
This work is concerned with the theory of initial and progressive enlargements of a reference filtration F with a random timeτ. We provide, under an equivalence assumption, slightly stronger than the absolute continuity assumption of Jacod, alternative proofs to results concerning canonical decomposition of an F -martingale in the enlarged filtrations. Also, we address martingales’ characterization in the enlarged filtrations in terms of martingales in the reference filtration, as well as predictable...
Cauchy approximation for sums of independent random variables.
Cauchy's equation on ?: futher results.
Cauchy's principal value of local times of Lévy processes with no negative jumps via continuous branching processes.
Causality and stochastic realization.
Cavity method in the spherical SK model
We develop a cavity method for the spherical Sherrington–Kirkpatrick model at high temperature and small external field. As one application we compute the limit of the covariance matrix for fluctuations of the overlap and magnetization.
Central and local limit theorems for excedances by conjugacy class and by derangement.
Central and non-central limit theorems for weighted power variations of fractional brownian motion
In this paper, we prove some central and non-central limit theorems for renormalized weighted power variations of order q≥2 of the fractional brownian motion with Hurst parameter H∈(0, 1), where q is an integer. The central limit holds for 1/2q<H≤1−1/2q, the limit being a conditionally gaussian distribution. If H<1/2q we show the convergence in L2 to a limit which only depends on the fractional brownian motion, and if H>1−1/2q we show the convergence in L2 to a stochastic integral...
Central extensions and stochastic processes associated with the Lie algebra of the renormalized higher powers of white noise
In the first part of the paper we discuss possible definitions of Fock representation of the *-Lie algebra of the Renormalized Higher Powers of White Noise (RHPWN). We propose one definition that avoids the no-go theorems and we show that the vacuum distribution of the analogue of the field operator for the n-th renormalized power of WN defines a continuous binomial process. In the second part of the paper we present without proof our recent results on the central extensions of RHPWN, its subalgebras...
Central limit problem and invariance principles on Banach spaces
Central limit problem for symmetric case: Convergence to non-Gaussian laws
Central limit theorem for a class of linear systems.
Central limit theorem for an additive functional of a Markov process, stable in the Wesserstein metric
We study the question of the law of large numbers and central limit theorem for an additive functional of a Markov processes taking values in a Polish space that has Feller property under the assumption that the process is asymptotically contractive in the Wasserstein metric.
Central limit theorem for coloured hard dimers.
Central Limit Theorem for Diffusion Processes in an Anisotropic Random Environment
We prove the central limit theorem for symmetric diffusion processes with non-zero drift in a random environment. The case of zero drift has been investigated in e.g. [18], [7]. In addition we show that the covariance matrix of the limiting Gaussian random vector corresponding to the diffusion with drift converges, as the drift vanishes, to the covariance of the homogenized diffusion with zero drift.
Central limit theorem for Gibbsian U-statistics of facet processes
A special case of a Gibbsian facet process on a fixed window with a discrete orientation distribution and with increasing intensity of the underlying Poisson process is studied. All asymptotic joint moments for interaction U-statistics are calculated and the central limit theorem is derived using the method of moments.