Convergence of a stochastic approximation version of the EM algorithm B Delyon, M Lavielle, E Moulines Annals of statistics, 94-128, 1999 | 914 | 1999 |

Using penalized contrasts for the change-point problem M Lavielle Signal processing 85 (8), 1501-1510, 2005 | 630 | 2005 |

Maximum likelihood estimation in nonlinear mixed effects models E Kuhn, M Lavielle Computational statistics & data analysis 49 (4), 1020-1038, 2005 | 629 | 2005 |

A statistical approach for array CGH data analysis F Picard, S Robin, M Lavielle, C Vaisse, JJ Daudin BMC bioinformatics 6 (1), 1-14, 2005 | 480 | 2005 |

Least‐squares estimation of an unknown number of shifts in a time series M Lavielle, E Moulines Journal of time series analysis 21 (1), 33-59, 2000 | 360 | 2000 |

Coupling a stochastic approximation version of EM with an MCMC procedure E Kuhn, M Lavielle ESAIM: Probability and Statistics 8, 115-131, 2004 | 349 | 2004 |

Detection of multiple changes in a sequence of dependent variables M Lavielle Stochastic Processes and their applications 83 (1), 79-102, 1999 | 257 | 1999 |

Mixed effects models for the population approach: models, tasks, methods and tools M Lavielle CRC press, 2014 | 240 | 2014 |

Detection of multiple change-points in multivariate time series M Lavielle, G Teyssiere Lithuanian Mathematical Journal 46 (3), 287-306, 2006 | 218 | 2006 |

Extension of the SAEM algorithm to left-censored data in nonlinear mixed-effects model: Application to HIV dynamics model A Samson, M Lavielle, F Mentré Computational Statistics & Data Analysis 51 (3), 1562-1574, 2006 | 190 | 2006 |

Estimation of population pharmacokinetic parameters of saquinavir in HIV patients with the MONOLIX software M Lavielle, F Mentré Journal of pharmacokinetics and pharmacodynamics 34 (2), 229-249, 2007 | 185 | 2007 |

An application of MCMC methods for the multiple change-points problem M Lavielle, E Lebarbier Signal processing 81 (1), 39-53, 2001 | 172 | 2001 |

Optimal segmentation of random processes M Lavielle IEEE Transactions on Signal Processing 46 (5), 1365-1373, 1998 | 163 | 1998 |

A comprehensive hepatitis C viral kinetic model explaining cure E Snoeck, P Chanu, M Lavielle, P Jacqmin, EN Jonsson, K Jorga, ... Clinical Pharmacology & Therapeutics 87 (6), 706-713, 2010 | 146 | 2010 |

Adaptive detection of multiple change-points in asset price volatility M Lavielle, G Teyssiere Long memory in economics, 129-156, 2007 | 109 | 2007 |

The SAEM algorithm for group comparison tests in longitudinal data analysis based on non‐linear mixed‐effects model A Samson, M Lavielle, F Mentré Statistics in medicine 26 (27), 4860-4875, 2007 | 92 | 2007 |

A note on BIC in mixed-effects models M Delattre, M Lavielle, MA Poursat Electronic journal of statistics 8 (1), 456-475, 2014 | 90 | 2014 |

The multiple change-points problem for the spectral distribution M Lavielle, C Ludeña Bernoulli, 845-869, 2000 | 90 | 2000 |

The use of the SAEM algorithm in MONOLIX software for estimation of population pharmacokinetic-pharmacodynamic-viral dynamics parameters of maraviroc in asymptomatic HIV subjects PLS Chan, P Jacqmin, M Lavielle, L McFadyen, B Weatherley Journal of pharmacokinetics and pharmacodynamics 38 (1), 41-61, 2011 | 85 | 2011 |

Parameter estimation in nonlinear mixed effect models using saemix, an R implementation of the SAEM algorithm E Comets, A Lavenu, M Lavielle Journal of Statistical Software 80, 1-41, 2017 | 83 | 2017 |