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Filter Theory - Theory and Applications
Check in the VVZ for a current information.
| Lecturer |
Prof. Dr. Josef Teichmann, Prof. Dr. Thorsten Schmidt |
Lecture |
Wed. 15-18 HG F 7 Wed. 18-19 HG F 7 |
| Coordinator |
Dr. Oleg Reichmann, Dr. Marcus Wunsch |
Exercises |
Exam date:
to be announced later.
Aims of the course
This course covers the theory of linear and non-linear filtering in various levels of generality. After studying theoretical foundations we will cover applications in mathematical finance, statistical aspects as well as numerical methods for solving filtering problems. Included are Filtering with continuous and point process observations (Linear filtering, Non-linear filtering, The general setting), Applications in statistics and interest rate theory and numerical methods like Markov chain approximations, Galerkin approximations or particle filtering.
Prerequisites
- probability theory,
- basic stochastic processes,
- basic statistics
R Links
R can be downloaded from CRAN
Literature
- A. Bain and D. Crisan (2009). Fundamentals of Stochastic Filtering. New York: Springer.
- R. Frey and T. Schmidt (2011). Filtering and incomplete information. Wiley.
- R. Lipster and A. Shiryaev (2001). Statistics of Random Processes: I - General Theory (2nd ed.). Berlin: Springer Verlag.
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