H. G. Matthies, A. Litvinenko, B. V. Rosic, E. Zander, Bayesian Parameter Estimation via Filtering and Functional Approximations, arXiv:1611.09293 , 2017
H. G. Matthies, A. Litvinenko, B. V. Rosic, E. Zander
Bayesian Parameter Estimation via Filtering and Functional Approximations
The inverse problem of determining parameters in a model by comparing some output of the model with observations is addressed. This is a description of what had to be done to use the Gauss-Markov-Kalman filter for the Bayesian estimation and updating of parameters in a computational model. This is a filter acting on random variables, and while its Monte Carlo variant --- the Ensemble Kalman Filter (EnKF) --- is fairly straightforward, we subsequently only sketch its implementation with the help of functional representations.