flexmix: Flexible Mixture Modeling

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.

Applications of finite mixtures of regression models 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

Vignettes Man pages API and functions Files

Package details
Author	Bettina Gruen [aut, cre] (<https://orcid.org/0000-0001-7265-4773>), Friedrich Leisch [aut] (<https://orcid.org/0000-0001-7278-1983>), Deepayan Sarkar [ctb] (<https://orcid.org/0000-0003-4107-1553>), Frederic Mortier [ctb], Nicolas Picard [ctb] (<https://orcid.org/0000-0001-5548-9171>)
Maintainer	Bettina Gruen <Bettina.Gruen@R-project.org>
License	GPL (>= 2)
Version	2.3-19
Package repository	View on CRAN
Installation	Install the latest version of this package by entering the following in R: `install.packages("flexmix")`