On the two-filter approximations of marginal smoothing distributions in general state space models
Statistics Theory
2016-05-30 v1 Probability
Statistics Theory
Abstract
A prevalent problem in general state space models is the approximation of the smoothing distribution of a state conditional on the observations from the past, the present, and the future. The aim of this paper is to provide a rigorous analysis of such approximations of smoothed distributions provided by the two-filter algorithms. We extend the results available for the approximation of smoothing distributions to these two-filter approaches which combine a forward filter approximating the filtering distributions with a backward information filter approximating a quantity proportional to the posterior distribution of the state given future observations.
Keywords
Cite
@article{arxiv.1605.08534,
title = {On the two-filter approximations of marginal smoothing distributions in general state space models},
author = {Thi Ngoc Minh Nguyen and Sylvain Le Corff and Eric Moulines},
journal= {arXiv preprint arXiv:1605.08534},
year = {2016}
}