Brownian Confidence Bands on Monte Carlo Output

W.S. Kendall 1 Jean-Michel Marin 1 C.P. Robert
1 SELECT - Model selection in statistical learning
Inria Saclay - Ile de France, LMO - Laboratoire de Mathématiques d'Orsay, CNRS - Centre National de la Recherche Scientifique : UMR
Abstract : When considering a Monte Carlo estimation procedure, the path produced by successive partial estimates is often used as a guide for informal convergence diagnostics. However the confidence region associated with that path cannot be derived simplistically from the confidence interval for the estimate itself. An asymptotically correct approach can be based on the Brownian motion approximation of the path, but no exact formula for the corresponding area-minimizing confidence region is yet known. We construct proxy regions based on local time arguments and consider numerical approximations. These are then available for a more incisive assessment of the Monte Carlo procedure and thence of the estimate itself.
Type de document :
Article dans une revue
Statistics and Computing, Springer Verlag (Germany), 2007, 17 (1), pp.1-10
Liste complète des métadonnées

https://hal.inria.fr/inria-00070571
Contributeur : Rapport de Recherche Inria <>
Soumis le : vendredi 19 mai 2006 - 20:54:43
Dernière modification le : jeudi 11 janvier 2018 - 06:22:14
Document(s) archivé(s) le : dimanche 4 avril 2010 - 21:29:29

Fichiers

Identifiants

  • HAL Id : inria-00070571, version 1

Collections

Citation

W.S. Kendall, Jean-Michel Marin, C.P. Robert. Brownian Confidence Bands on Monte Carlo Output. Statistics and Computing, Springer Verlag (Germany), 2007, 17 (1), pp.1-10. 〈inria-00070571〉

Partager

Métriques

Consultations de la notice

255

Téléchargements de fichiers

228