The main goal of this project is to study several statistical and stochastic models for time- dependent measures using parametric and non-parametric approaches. In particular, we will study the inference in complex mixed effects models, we will propose novel segmentation models for multiple series, non-parametric methods in dependent models and stochastic differential equations and their applications in population dynamics and finance.

The specific scientific goals of this project are as follows:

1. To propose an estimation procedure in high dimensional mixed effects models

2. To develop new statistical tools for degration process using mixed effects models

3. To propose a Bayesian approach for the segmentation of multiple series using a semi-

   parametric model

4. To study non-parametric methods in dependent models

5. To study stochastic differential equations and their applications in population dynamics

   and finance