MONOLIX is a free software dedicated to the analysis of non linear mixed effects models. The objective of this software is to perform: parameter estimation, model selection, goodness of fit plots and, data simulation.
Keywords for this software
References in zbMATH (referenced in 7 articles )
Showing results 1 to 7 of 7.
- Grenier, Emmanuel; Helbert, Celine; Louvet, Violaine; Samson, Adeline; Vigneaux, Paul: Population parametrization of costly black box models using iterations between SAEM algorithm and Kriging (2018)
- Lavielle, Marc: Mixed effects models for the population approach. Models, tasks, methods and tools. With contributions by Kevin Bleakley (2015)
- Lavielle, Marc; Mbogning, Cyprien: An improved SAEM algorithm for maximum likelihood estimation in mixtures of non linear mixed effects models (2014)
- Delattre, Maud; Lavielle, Marc: Coupling the SAEM algorithm and the extended Kalman filter for maximum likelihood estimation in mixed-effects diffusion models (2013)
- Leonov, Sergei; Aliev, Alexander: Optimal design for population PK/PD models (2012)
- Lavielle, Marc; Samson, Adeline; Fermin, Ana Karina; Mentré, France: Maximum likelihood estimation of long-term HIV dynamic models and antiviral response (2011)
- Duval, Mylène; Robert-Granié, Christèle; Foulley, Jean-Louis: Estimation of heterogeneous variances in nonlinear mixed models via the SAEM-MCMC algorithm with applications to growth curves in poultry (2009)
Further publications can be found at: https://www.projet-plume.org/en/relier/monolix