| Comparison of resampling schemes for particle filtering R Douc, O Cappé ISPA 2005. Proceedings of the 4th International Symposium on Image and …, 2005 | 1306 | 2005 |
| Adaptive importance sampling in general mixture classes O Cappé, R Douc, A Guillin, JM Marin, CP Robert Statistics and Computing 18, 447-459, 2008 | 371 | 2008 |
| Markov chains: Basic definitions R Douc, E Moulines, P Priouret, P Soulier, R Douc, E Moulines, P Priouret, ... Markov Chains, 3-25, 2018 | 368 | 2018 |
| Nonlinear time series: Theory, methods and applications with R examples R Douc, E Moulines, D Stoffer CRC press, 2014 | 337 | 2014 |
| Asymptotic properties of the maximum likelihood estimator in autoregressive models with Markov regime R Douc, E Moulines, T Rydén | 325 | 2004 |
| Sequential Monte Carlo smoothing with application to parameter estimation in nonlinear state space models J Olsson, O Cappé, R Douc, E Moulines | 212 | 2008 |
| Limit theorems for weighted samples with applications to sequential Monte Carlo methods R Douc, E Moulines ESAIM: Proceedings 19, 101-107, 2007 | 212 | 2007 |
| Sequential Monte Carlo smoothing for general state space hidden Markov models R Douc, A Garivier, E Moulines, J Olsson | 200 | 2011 |
| Practical drift conditions for subgeometric rates of convergence R Douc, G Fort, E Moulines, P Soulier | 193 | 2004 |
| Subgeometric rates of convergence of f-ergodic strong Markov processes R Douc, G Fort, A Guillin Stochastic processes and their applications 119 (3), 897-923, 2009 | 189 | 2009 |
| Convergence of adaptive mixtures of importance sampling schemes R Douc, A Guillin, JM Marin, CP Robert | 187 | 2007 |
| Asymptotics of the maximum likelihood estimator for general hidden Markov models R Douc, C Matias | 153 | 2001 |
| Consistency of the maximum likelihood estimator for general hidden Markov models R Douc, E Moulines, J Olsson, R Van Handel | 148 | 2011 |
| Minimum variance importance sampling via population Monte Carlo R Douc, A Guillin, JM Marin, CP Robert ESAIM: Probability and Statistics 11, 427-447, 2007 | 121 | 2007 |
| Quantitative bounds on convergence of time-inhomogeneous Markov chains R Douc, E Moulines, JS Rosenthal Annals of Applied Probability, 1643-1665, 2004 | 108 | 2004 |
| Ergodicity of observation-driven time series models and consistency of the maximum likelihood estimator R Douc, P Doukhan, E Moulines Stochastic Processes and their Applications 123 (7), 2620-2647, 2013 | 87 | 2013 |
| Optimality of the auxiliary particle filter R Douc, E Moulines, J Olsson Probability and Mathematical Statistics 29 (1), 1-28, 2009 | 72 | 2009 |
| Scaling analysis of multiple-try MCMC methods M Bédard, R Douc, E Moulines Stochastic Processes and their Applications 122 (3), 758-786, 2012 | 68 | 2012 |
| Uniform ergodicity of the particle Gibbs sampler F Lindsten, R Douc, E Moulines Scandinavian Journal of Statistics 42 (3), 775-797, 2015 | 66 | 2015 |
| Forgetting the initial distribution for hidden Markov models R Douc, G Fort, E Moulines, P Priouret Stochastic processes and their applications 119 (4), 1235-1256, 2009 | 65 | 2009 |
Eric MoulinesProfesseur, Ecole Polytechnique, Membre de l'Académie des SciencesVerified email at polytechnique.edu