This project course on advanced statistical modeling is a compulsory part of the MSc program in statistics. The content of the course presumes a mathematical level corresponding to this MSc program, and consists of:

• An advanced subject in statistical modeling.
• Independent literature studies.
• Theoretical work on models and methods relevant for data analysis.
• Practical work on statistical modeling, implementation and/or data analysis.
• Organization of a larger project and writing of reports.
• Written presentation of methodology, data analysis and results.

The exact subjects and how the different components above are weighed depend on the supervisors assigned to the course. A list of projects will be offered at the beginning of the course, and the participants will choose one from that list.

Examples of advanced subjects are:

• Classification and machine learning.
• High-dimensional statistics.
• Functional data analysis.
• Bayesian analysis and Markov Chain Monte Carlo (MCMC).
• Mixed and hierarchical models.
• Graphical models.
• Applied biostatistics.
• Causal inference.
• Dynamical systems.