Department of Mathematics

Dr. Moritz Schauer, Chalmers University of Technology: "Smoothing and inference for high dimensional diffusions"

Dec 12, 2019 from 10:15 AM to 11:45 AM

LMS 4 - Raum 325 - Seminarhörsaal


Suppose we discretely observe a diffusion process and we wish to estimate parameters appearing in either the drift coefficient or the diffusion coefficient. We derive a representation of the conditional distribution given observations as change of measure to be embedded as step in a Monte-Carlo procedure to estimate those parameters. 

The technique is based on solving the reverse time filtering problem for a linear approximation of the diffusion and a change of measure to correct for the difference between the linear approximation and the true smoothed process.

We apply this to the problem of tracking convective cloud systems from satellite data with low time resolution.


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