FlexMix implements a general framework for finite mixtures of regression models using the EM algorithm. FlexMix provides the E-step and all data handling, 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: | 2.2-0 |
| Depends: | lattice, modeltools (≥ 0.2-16), multcomp |
| Imports: | methods, stats, stats4 |
| Suggests: | MASS, ellipse, grid, mvtnorm, nnet |
| Date: | 2008-10-03 |
| Author: | Friedrich Leisch and Bettina Gruen |
| Maintainer: | Bettina Gruen <Bettina.Gruen at wu-wien.ac.at> |
| License: | GPL-2 |
| URL: | http://www.aasc.or.at/mixtures |
| In views: | Cluster |
| CRAN checks: | flexmix results |
Downloads:
| Package source: | flexmix_2.2-0.tar.gz |
| MacOS X binary: | flexmix_2.2-0.tgz |
| Windows binary: | flexmix_2.2-0.zip |
| Reference manual: | flexmix.pdf |
| Vignettes: |
FlexMix: A General Framework for Finite Mixture Models and Latent Class Regression in R FlexMix Version 2: Finite Mixtures with Concomitant Variables and Varying and Constant Parameters Applications of finite mixtures of regression models |
| News/ChangeLog: | NEWS |
| Old sources: | flexmix archive |