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Title of Journal: Stat Comput

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Abbravation: Statistics and Computing

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Springer US

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DOI

10.1016/0026-2692(95)98909-b

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1573-1375

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Optimal SIR algorithm vs fully adapted auxiliary

Authors: Yohan Petetin François Desbouvries
Publish Date: 2012/08/11
Volume: 23, Issue: 6, Pages: 759-775
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Abstract

Particle filters PF and auxiliary particle filters APF are widely used sequential Monte Carlo SMC techniques In this paper we comparatively analyse from a non asymptotic point of view the Sampling Importance Resampling SIR PF with optimal conditional importance distribution CID and the fully adapted APF FA We compute the finite samples conditional second order moments of Monte Carlo MC estimators of a moment of interest of the filtering pdf and analyse under which circumstances the FAbased estimator outperforms or not the optimal Sequential Importance Sampling SISbased one Our analysis is local in the sense that we compare the estimators produced by one time step of the different SMC algorithms starting from a common set of weighted points This analysis enables us to propose a hybrid SIS/FA algorithm which automatically switches at each time step from one loop to the other We finally validate our results via computer simulations

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  2. A focused information criterion for graphical models
  3. An advancement in clustering via nonparametric density estimation
  4. Clustering via nonparametric density estimation
  5. Sequential importance sampling of binary sequences
  6. Deletion diagnostics for marginal mean and correlation model parameters in estimating equations
  7. Boosted coefficient models
  8. Non-parametric maximum likelihood estimation of interval-censored failure time data subject to misclassification
  9. Gaussian proposal density using moment matching in SMC methods
  10. Bayesian inference for Heston-STAR models
  11. Parsimonious Gaussian mixture models
  12. Efficient estimation of variance components in nonparametric mixed-effects models with large samples
  13. On the computation of the noncentral F and noncentral beta distribution
  14. A new variable importance measure for random forests with missing data
  15. Complement to a comparative analysis of heuristics for the  p -median problem
  16. Likelihood-free parallel tempering
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