| DIYABC v2. 0: a software to make approximate Bayesian computation inferences about population history using single nucleotide polymorphism, DNA sequence and microsatellite data JM Cornuet, P Pudlo, J Veyssier, A Dehne-Garcia, M Gautier, R Leblois, ... Bioinformatics 30 (8), 1187-1189, 2014 | 1108 | 2014 |
| Approximate Bayesian computational methods JM Marin, P Pudlo, CP Robert, RJ Ryder Statistics and computing 22 (6), 1167-1180, 2012 | 1019 | 2012 |
| Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation JM Cornuet, F Santos, MA Beaumont, CP Robert, JM Marin, DJ Balding, ... Bioinformatics 24 (23), 2713-2719, 2008 | 838 | 2008 |
| Adaptive approximate Bayesian computation MA Beaumont, JM Cornuet, JM Marin, CP Robert Biometrika 96 (4), 983-990, 2009 | 811 | 2009 |
| Bayesian core: a practical approach to computational Bayesian statistics JM Marin Springer, 2007 | 620 | 2007 |
| Bayesian modelling and inference on mixtures of distributions JM Marin, K Mengersen, CP Robert Handbook of statistics 25, 459-507, 2005 | 616 | 2005 |
| Population monte carlo O Cappé, A Guillin, JM Marin, CP Robert Journal of Computational and Graphical Statistics, 2004 | 608 | 2004 |
| Unraveling cell type–specific and reprogrammable human replication origin signatures associated with G-quadruplex consensus motifs E Besnard, A Babled, L Lapasset, O Milhavet, H Parrinello, C Dantec, ... Nature structural & molecular biology 19 (8), 837-844, 2012 | 488 | 2012 |
| Lack of confidence in approximate Bayesian computation model choice CP Robert, JM Cornuet, JM Marin, NS Pillai Proceedings of the National Academy of Sciences 108 (37), 15112-15117, 2011 | 437 | 2011 |
| Reliable ABC model choice via random forests P Pudlo, JM Marin, A Estoup, JM Cornuet, M Gautier, CP Robert Bioinformatics 32 (6), 859-866, 2016 | 411 | 2016 |
| Adaptive importance sampling in general mixture classes O Cappé, R Douc, A Guillin, JM Marin, CP Robert Statistics and Computing 18, 447-459, 2008 | 368 | 2008 |
| Adaptive multiple importance sampling JM CORNUET, JM MARIN, A Mira, CP Robert Scandinavian Journal of Statistics 39 (4), 798-812, 2012 | 317 | 2012 |
| ABC random forests for Bayesian parameter inference L Raynal, JM Marin, P Pudlo, M Ribatet, CP Robert, A Estoup Bioinformatics 35 (10), 1720-1728, 2019 | 218 | 2019 |
| ABC likelihood-free methods for model choice in Gibbs random fields A Grelaud, JM Marin, CP Robert, F Rodolphe, JF Taly | 218* | 2009 |
| Convergence of adaptive mixtures of importance sampling schemes R Douc, A Guillin, JM Marin, CP Robert | 187 | 2007 |
| Deciphering the Routes of invasion of Drosophila suzukii by Means of ABC Random Forest A Fraimout, V Debat, S Fellous, RA Hufbauer, J Foucaud, P Pudlo, ... Molecular biology and evolution 34 (4), 980-996, 2017 | 180 | 2017 |
| Relevant statistics for Bayesian model choice JM Marin, NS Pillai, CP Robert, J Rousseau Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2014 | 164 | 2014 |
| Estimation of demo‐genetic model probabilities with Approximate Bayesian Computation using linear discriminant analysis on summary statistics A Estoup, E Lombaert, JM MARIN, T Guillemaud, P Pudlo, CP Robert, ... Molecular ecology resources 12 (5), 846-855, 2012 | 132 | 2012 |
| Bayesian essentials with R JM Marin, CP Robert Springer, 2014 | 126 | 2014 |
| 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 |
Christian RobertUniversité Paris Dauphine, PSL & University of WarwickAdresse e-mail validée de ceremade.dauphine.fr
