arXiv · 1605.08534
On the two-filter approximations of marginal smoothing distributions in general state space models
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.
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Thi Ngoc Minh Nguyen, Sylvain Le Corff, Eric Moulines. 2016-05-27. On the two-filter approximations of marginal smoothing distributions in general state space models. https://arxiv.org/abs/1605.08534
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