FlexMix: An R Package for Flexible Mixture Modeling
Package flexmix implements a general framework for finite mixtures of regression models using the EM algorithm. The package 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.
Package sources and binaries of the release version on
Key publications presenting and discussing the implementation are:
Friedrich Leisch. FlexMix: A general framework for finite mixture models and latent class regression in R. Journal of Statistical Software, 11(8), 1-18, October 2004. [ http ]
Bettina Grün and Friedrich Leisch. Fitting finite mixtures of generalized linear regressions in R. Computational Statistics & Data Analysis, 51(11):5247-5252, July 2007. [DOI ]
Bettina Grün and Friedrich Leisch. Flexmix version 2: Finite mixtures with concomitant variables and varying and constant parameters. Journal of Statistical Software, 28(4):1-35, September 2008. [ http ]