Nonlinear statistical inverse problems with random observations (A04)

• Subject Area: Mathematics
• Term: since 2017
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 318763901

The project deals with nonlinear statistical inverse problems. The goal is to estimate from random observations the functional relation between observable covariates and intrinsic (unobservable) parameters of a system. The system depends on the intrinsic parameters through a specific model, e.g. a differential equation. Mechanistic modelling approaches from pharmacokinetics serve as a specific application. We will develop frequentist and Bayesian nonparametric estimators of the unknown functional relation. Properties of the estimators, e.g. computational efficiency and uncertainty quantification, will be analysed.

• DFG Programme: Collaborative Research Centres
• Subproject of: SFB 1294: Data Assimilation – The Seamless Integration of Data and Models
• International Connection: France
• Applicant Institution: Universität Potsdam
• Project Heads: Professor Dr. Gilles Blanchard, until 6/2021; Professor Dr. Wilhelm Huisinga; Professor Dr. Han Cheng Lie, since 7/2021; Professor Dr. Markus Reiß