Parameter Uncertainty in the Kalman-Bucy Filter

Abstract

In standard treatments of stochastic filtering one first has to estimate the values of the parameters of the model. Simply running the filter without considering the reliability of this estimate does not take into account this additional source of statistical uncertainty. We propose an approach to address this problem when working with the continuous-time Kalman-Bucy filter. We show how our approach may be reformulated as an optimal control problem, and proceed to analyse the corresponding value function in some detail. In particular we present a novel uniqueness result for the associated Hamilton-Jacobi-Bellman equation.