Section: New Results

Stochastic modelling

Participants: T. Bastogne, P. Vallois, S. Wantz-Mezieres, L. Batista, A. Gégout-Petit

Because of the observation of longitudinal data for each subject in medicine, we have to care about the random effect due to the subject and to choose adapted models like mixed effect models [39], [40]. We recently improved this methodology for the analysis of data collected in vivo for growth tumor for the biopharmaceutical company Transgene. The problem was to measure the differential effect of treatments (different molecules and doses) on the dynamics of the tumor taking into account the effect of censoring [10].

In the framework of the esca-illness of vines, we developed different spatial models and spatio-temporal models for different purposes: (1) study the distribution and the dynamics of esca vines in order to tackle the aggregation and the potential spread of the illness (2) propose a spatio-temporal model in order to capture the dynamics of cases and measure the effects of environmental covariates. For purpose (1), we propose different tests based on the join count statistics [6].