Issue |
ESAIM: Proc.
Volume 19, 2007
Conference Oxford sur les méthodes de Monte Carlo séquentielles
|
|
---|---|---|
Page(s) | 85 - 100 | |
DOI | https://doi.org/10.1051/proc:071912 | |
Published online | 30 October 2007 |
Combined use of importance weights and resampling weights in sequential Monte Carlo methods
IRISA / INRIA, Campus de Beaulieu, 35042 RENNES Cédex, France
A particle approximation of Feynman–Kac distributions is presented here, that combines SIS and SIR algorithms in the sense that only a part of the importance weights is used for resampling, and two different approaches are proposed to analyze its performance. The first approach is based on a representation in terms of path–space distributions, and could be used to analyze the joint particle approximation of distributions for a reference model and several alternate models at the same time. The second approach, which is of independent interest and seems very promising, is based on a representation in terms of a multiplicative functional, and could be used to analyze particle approximation with adaptive resampling schemes.
© EDP Sciences, ESAIM, 2007
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.