Volume 19, 2007Conference Oxford sur les méthodes de Monte Carlo séquentielles
|Page(s)||85 - 100|
|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
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