A new approach to particle based smoothed marginal MAP
Saikat Saha, Pranab Kumar Mandal, Amitava Bagchi · University of Twente Research Information · 2008
We present here a new method of finding the MAP state estima-tor from the weighted particles representation of marginal smoother distribution. This is in contrast to the usual practice, where the particle with the highest weight is selected as the MAP, although the latter is not necessarily the most probable state estimate. The method developed here uses only particles with corresponding fil-tering and smoothing weights. We apply this estimator for finding the unknown initial state of a dynamical system and addressing the parameter estimation problem. 1.