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: 2.3-10
Depends: R (≥ 2.15.0), lattice
Imports: grid, methods, modeltools (≥ 0.2-16), stats, stats4
Suggests: MASS, codetools, diptest, ellipse, gclus, lme4, mgcv (≥ 1.6-1), mlbench, mlogit, multcomp, mvtnorm, nnet, survival
Published: 2013-02-13
Author: Bettina Gruen and Friedrich Leisch
Maintainer: Bettina Gruen <Bettina.Gruen at jku.at>
License: GPL (≥ 2) (see file LICENSE)
NeedsCompilation: no
Citation: flexmix citation info
In views: Cluster, Environmetrics
CRAN checks: flexmix results

Downloads:

Package source: flexmix_2.3-10.tar.gz
MacOS X binary: flexmix_2.3-10.tgz
Windows binary: flexmix_2.3-10.zip
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
News/ChangeLog:NEWS
Old sources: flexmix archive

Reverse dependencies:

Reverse depends: fpc, GOSim, psychomix, tlemix
Reverse imports: betareg, tlemix
Reverse suggests: betareg, catdata, HSAUR, HSAUR2, tlemix
Reverse enhances: clue