The purpose of this workshop (which is a continuation of DYNSTOCH meetings) is to stimulate research in statistical inference for continuous time stochastic processes. This branch of mathematical statistics attracts more and more attention of the statisticians and probabilists because first: the real systems are often well described by the continuous time mathematical models (point processes, diffusion processes, stochastic differential equations with partial derivatives, stable processes etc.) and the second: the diversity of the models and the diversity of the statements of the statistical problems make these models quite attractive for the mathematicians because all these allow to obtain many new results which sometimes have no analog in discrete time models.

Note that solutions obtained for continuous time models can be valid for discrete schemes of observation too. The computer realizations of the statistical algorithms (real data applications) requires that a special attention have to be payed to the effects due to discretization of continuous-time trajectories. Therefore, we wait that one (important) part of the talks will be devoted to statistical inference for discrete time observations (of continuous time systems).

Note as well, that statistical problems for stochastic processes are in the field of interests of the research teams of the universities of Rennes, Angers, Le Mans and Brest, hence this workshop can be considered as a current three-days seminaire triangulaire traditionally organized by these universities.