Some ideas for bias and variance reduction in the splitting algorithm for diffusion processes

Abstract : In this article, we highlight a bias induce by the discretization of the sample Markov paths in the splitting algorithm. Consequently we propose to correct this bias using a deformation of the intermediate regions. Moreover, we propose two estimation methods of the optimal regions in the splitting algorithm to minimise the splitting variance. One is connected with partial differential equation approach, the other one is based on the discretization of the state space of the process.
Type de document :
Article dans une revue
Journal of Computational Science, Elsevier, 2015, 11, pp.58--68. 〈10.1016/j.jocs.2015.09.005〉
Liste complète des métadonnées

https://hal.inria.fr/hal-01253763
Contributeur : Francois Le Gland <>
Soumis le : lundi 11 janvier 2016 - 12:41:09
Dernière modification le : mardi 19 juin 2018 - 11:12:07

Identifiants

Citation

Damien Jacquemart, Jérôme Morio, François Le Gland. Some ideas for bias and variance reduction in the splitting algorithm for diffusion processes. Journal of Computational Science, Elsevier, 2015, 11, pp.58--68. 〈10.1016/j.jocs.2015.09.005〉. 〈hal-01253763〉

Partager

Métriques

Consultations de la notice

342