A general framework for finite mixtures of regression models using the EM algorithm is implemented. The E-step and all data handling are provided, while the M-step can be supplied by the user to easily define new models. Existing drivers implement mixtures of standard linear models, generalized linear models and model-based clustering.
| Version: | 2.3-20 |
| Depends: | R (≥ 2.15.0),lattice |
| Imports: | graphics, grid, grDevices, methods,modeltools (≥ 0.2-16),nnet, stats, stats4, utils |
| Suggests: | actuar,codetools,diptest,Ecdat,ellipse,gclus,glmnet,lme4 (≥ 1.1),MASS,mgcv (≥ 1.8-0),mlbench,multcomp,mvtnorm,SuppDists,survival |
| Published: | 2025-02-28 |
| DOI: | 10.32614/CRAN.package.flexmix |
| Author: | Bettina Gruen [aut, cre], Friedrich Leisch [aut], Deepayan Sarkar [ctb], Frederic Mortier [ctb], Nicolas Picard [ctb] |
| Maintainer: | Bettina Gruen <Bettina.Gruen at R-project.org> |
| License: | GPL-2 |GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Citation: | flexmix citation info |
| Materials: | NEWS |
| In views: | Cluster,Environmetrics,Psychometrics |
| CRAN checks: | flexmix results |