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Focus on particle methods| old_uid | 9178 |
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| title | Focus on particle methods |
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| start_date | 2010/10/21 |
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| schedule | 15h-17h |
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| online | no |
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| summary | An introduction to particle methods for filtering and smoothing Sylvain Le Corff (Telecom ParisTech): Error bounds in forward filtering backward smoothing (joint work with Cyrille Dubarry) [Abstract : Approximating joint smoothing distributions using particle-based methods is a well-known issue in statistical inference when operating on general state space hidden Markov models (HMM). In this paper, we focus on non-asymptotic bounds for the error generated by the computation of smoothed additive functionals. More precisely, this contribution provides new results on the forward filtering backward smoothing (FFBS) error?s Lq-norms under appropriate mixing conditions on the Markov kernel?s probability density function. The algorithm used has a computational complexity depending linearly on TN where T is the number of observations and N the number of particles. The main improvement ... |
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| responsibles | Biau, Stoltz, Massart |
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