Correction : «Filtrations quotients de la filtration brownienne»
Correction : « Intégrales stochastiques par rapport aux processus de Wiener ou de Poisson »
Correction : « is not a semimartingale»
Correction of the title of the paper in CMUC 20 (1979), 173-182
Correction : “Pedagogic notes on the Barrier theorem”
Correction : “Processus de Galton-Watson”
Correction : «Temps local pour les martingales à deux indices par rapport à sa variation quadratique»
Corrections : “Penetration times and Skorohod stopping”
Countable representation for infinite dimensional diffusions derived from the two-parameter Poisson-Dirichlet process.
Coupling a branching process to an infinite dimensional epidemic process***
Branching process approximation to the initial stages of an epidemic process has been used since the 1950's as a technique for providing stochastic counterparts to deterministic epidemic threshold theorems. One way of describing the approximation is to construct both branching and epidemic processes on the same probability space, in such a way that their paths coincide for as long as possible. In this paper, it is shown, in the context of a Markovian model of parasitic infection, that coincidence...
Coupling iterated Kolmogorov diffusions.
Covariance and relaxation time in finite Markov chains.
Covariance structure of wide-sense Markov processes of order k ≥ 1
A notion of a wide-sense Markov process of order k ≥ 1, , is introduced as a direct generalization of Doob’s notion of wide-sense Markov process (of order k=1 in our terminology). A base for investigation of the covariance structure of is the k-dimensional process . The covariance structure of is considered in the general case and in the periodic case. In the general case it is shown that iff is a k-dimensional WM(1) process and iff the covariance function of has the triangular property....
Criteria of regularity at the end of a tree
Critical branching diffusions : proper normalization and conditioned limit
C-semigroups on Banach spaces and functional inequalities
Cut-off for large sums of graphs
If is the combinatorial Laplacian of a graph, converges to a matrix with identical coefficients. The speed of convergence is measured by the maximal entropy distance. When the graph is the sum of a large number of components, a cut-off phenomenon may occur: before some instant the distance to equilibrium tends to infinity; after that instant it tends to . A sufficient condition for cut-off is given, and the cut-off instant is expressed as a function of the gap and eigenvectors of components....
Cutoff for samples of Markov chains
Cutoff for samples of Markov chains
We study the convergence to equilibrium of n-samples of independent Markov chains in discrete and continuous time. They are defined as Markov chains on the n-fold Cartesian product of the initial state space by itself, and they converge to the direct product of n copies of the initial stationary distribution. Sharp estimates for the convergence speed are given in terms of the spectrum of the initial chain. A cutoff phenomenon occurs in the sense that as n tends to infinity, the total variation...
Cycle time of stochastic max-plus linear systems.