Inference in Stochastic Processes



Presentation Members For members only

In general, observations from real life are not independent. This fact links together research themes of this team. We are therefore interested in the development of dependency theory to obtain moment and exponential inequalities, TCL functional limit and make functional estimation.

Systems of interacting particles and some issues arising from problems of mathematical physics concerning the behaviour of the interface between two phases transitions also hold the attention of some researchers of our team.

Our research on stochastic processes is aimed at discrete-time integer values as well as continuous time processes and real or complex values as it can be seen in the publications of the members of our team.

Sampling plans for the prediction of stochastic processes and generalizing the spatial case are also issues we address. The non-parametric estimation, with kernels, local polynomials, the regression function from repeated observations for an autocorrelated error process was also considered as well as estimators of the regression operator for functional data.

Karim Benhenni
Chair of the ISP Team


Previous chair Corinne Berzin