Seminar Computational and Applied Mathematics

Stochastic filtering is an important estimation problem for time series. In this talk, we present a class of filters that represent the filtering distributions by their moments. The key enablement is a quadrature method that uses orthonormal polynomials spanned by the moments. We show that this moment-based filter is asymptotically exact in the order of moments, and that the filter is also computationally efficient and is in line with the state of the art.