Description

The project ISULO is subdivided into 6 workpackages. The first concerns the project management. The WP 2 and 3 are associated to research works. The integration of prior knowledge into statistical models allows to improve the identification of relevant variables. In this objective, the WP2 proposes Bayesian variable selection approaches to integrate prior knowledge from experimental studies or computed. The WP3 focuses on the analysis of longitudinal data with a double objective of grouping individuals with similar profiles over time and of selecting the relevant variables related to this clustering. The proposed model will combine variable selection and partitioning methods. In the WP4 the data provided by the partners are analyzed with the developed methods or by innovative existing methods. All of the used methods are transferred to the partners with hands-on demonstration with R via the WP5. Finally, through the WP6, the developed methods as well as the data analyses are disseminated in international congress or in publications.