Other publications


    C. Dubarry and R. Douc Particle approximation improvement of the joint smoothing distribution with on-the-fly variance estimation. http://arxiv.org/pdf/1107.5524.pdf


  • R.Douc, E. Moulines, P. Soulier. Subgeometric ergodicity of Markov chains‘. In the book: Dependence in Probability and Statistics, Series: Lecture notes in
    Statistics, Springer Vol. 187. P. Bertail, P. Doukhan, P. Soulier (Eds), 2006.
  • R. Douc, E. Moulines: Analysis of Sequential Monte Carlo Methods. In the book: Inference in Hidden Markov Models, Series: Springer series in statistics, Springer. O. Cappé, E. Moulines and T. Ryden, 2005.


  • Dubarry, C.; Douc, R.;
    Improving particle approximations of the joint smoothing distribution with linear computational cost.
    Statistical Signal Processing Workshop (SSP), 2011, Pages: 209 – 212
  • Maire, F.; Lefebvre, S.; Moulines, E.; Douc, R.
    Aircraft classification with a low resolution infrared sensor
    Statistical Signal Processing Workshop (SSP), 2011, Pages: 761 – 764
  • Olsson, Jimmy; Moulines, Eric; Douc, Randal;
    Improving the Performance of the Two-Stage Sampling Particle Filter: A Statistical Perspective,
    Statistical Signal Processing, 2007. Pages: 284 – 288
  • O. Cappé, R. Douc and E. Moulines ,
    Comparison of Resampling Schemes for Particle Filtering.
    In 4th International Symposium on Image and Signal Processing and Analysis (ISPA), Zagreb, Croatia, sep 2005.
  • R. Douc, E. Moulines and T. Rydén,
    Asymptotic Properties of the Maximum Likelihood Estimator in Autoregressive Models with Markov Regime,
    Proceedings {INFORMS} 2001, 2001
  • O. Cappé, R. Douc, E. Moulines and C. Robert,
    Bayesian analysis of overdispersed count data with applications to teletraffic monitoring,
    Proceedings of COMPSTAT, 215–220, 1998


  • PHD Report (2001): Problèmes statistiques pour des modèles à variables latentes: propriétés asymptotique de l’Estimateur du Maximum de
  • HABILITATION Repor (2007)t: Estimation dans des modèles à variables latentes, méthodes particulaires et convergence des chaînes de Markov.