flexmix: Flexible Mixture Modeling

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: 2.3-11
Depends: R (≥ 2.15.0), lattice
Imports: grid, methods, modeltools (≥ 0.2-16), nnet, stats, stats4
Suggests: codetools, diptest, ellipse, gclus, lme4 (≥ 1.0), MASS, mgcv (≥ 1.6-1), mlbench, mlogit, multcomp, mvtnorm, survival
Published: 2013-09-27
Author: Bettina Gruen [aut, cre], Friedrich Leisch [aut], Deepayan Sarkar [ctb]
Maintainer: Bettina Gruen <Bettina.Gruen at jku.at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: flexmix citation info
Materials: NEWS
In views: Cluster, Environmetrics
CRAN checks: flexmix results

Downloads:

Reference manual: flexmix.pdf
Vignettes: Complement: Finite Mixture Model Diagnostics Using Resampling Methods
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
Package source: flexmix_2.3-11.tar.gz
MacOS X binary: flexmix_2.3-11.tgz
Windows binary: flexmix_2.3-11.zip
Old sources: flexmix archive

Reverse dependencies:

Reverse depends: fpc, psychomix
Reverse imports: betareg, expands
Reverse suggests: catdata, HSAUR, HSAUR2, HSAUR3, rebmix, tlemix
Reverse enhances: clue