Monte Carlo fixed-lag smoothing in state-space models
Applications
2015-06-17 v1
Abstract
This paper presents an algorithm for Monte Carlo fixed-lag smoothing in state-space models defined by a diffusion process observed through noisy discrete-time measurements. Based on a particles approximation of the filtering and smoothing distributions, the method relies on a simulation technique of conditioned diffusions. The proposed sequential smoother can be applied to general non linear and multidimensional models, like the ones used in environmental applications. The smoothing of a turbulent flow in a high-dimensional context is given as a practical example.
Cite
@article{arxiv.1310.1267,
title = {Monte Carlo fixed-lag smoothing in state-space models},
author = {Anne Cuzol and Etienne Mémin},
journal= {arXiv preprint arXiv:1310.1267},
year = {2015}
}