StUDyS: Developing crucial Statistical methods for Understanding major complex Dynamic Systems in natural, biomedical and social sciences (R-4152)

Stochastic systems are influenced by internal characteristics of the system, but may as well depend on (interactions with) external factors, and may evolve over time and/or space. The main goal of this IAP-network is to develop statistical methods that are crucial for complete understanding of certain classes of complex dynamic systems, and to use these to answer challenging questions in focused applications. Due to advances in technology, the complexity of the total data structure is often quite involved: different types of data, several sources of information on a same subsystem, few measurements on a large number of characteristics,... Although more and/or diverse information is to be applauded for, consequently, extraction of the important information from it becomes a real challenge. The main objectives in the network is to study the associations and dependencies in complex systems, to study the different dynamics in complex systems, to develop multivariate models and methods for hierarchically structured data, to study the dynamics of a stochastic system and the impact of non-observed characteristics and variable and model selection of high-dimensional data.

Keywords:Advanced data structures, complex stochastic systems, Statistical methods

Disciplines:Applied mathematics in specific fields, Statistics and numerical methods

Project type:Collaboration project