Non-failable approximation method for conditioned distributions
Probability
2016-06-30 v1
Abstract
We consider a general method for the approximation of the distribution of a process conditioned to not hit a given set. Existing methods are based on particle system that are failable, in the sense that, in many situations , they are not well defined after a given random time. We present a method based on a new particle system which is always well define. Moreover , we provide sufficient conditions ensuring that the particle method converges uniformly in time. We also show that this method provides an approximation method for the quasi-stationary distribution of Markov processes. Our results are illustrated by their application to a neutron transport model.
Cite
@article{arxiv.1606.08978,
title = {Non-failable approximation method for conditioned distributions},
author = {William Oçafrain and Denis Villemonais},
journal= {arXiv preprint arXiv:1606.08978},
year = {2016}
}