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.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("flexmix")

2.3-15 by Bettina Gruen, 2 months ago


Browse source code at https://github.com/cran/flexmix


Authors: Bettina Gruen [aut, cre] , Friedrich Leisch [aut] , Deepayan Sarkar [ctb] , Frederic Mortier [ctb] , Nicolas Picard [ctb]


Documentation:   PDF Manual  


Task views: Cluster Analysis & Finite Mixture Models, Analysis of Ecological and Environmental Data, Psychometric Models and Methods


GPL (>= 2) license


Imports graphics, grid, grDevices, methods, modeltools, nnet, stats, stats4, utils

Depends on lattice

Suggests actuar, codetools, diptest, Ecdat, ellipse, gclus, glmnet, lme4, MASS, mgcv, mlbench, multcomp, mvtnorm, SuppDists, survival


Imported by DAC, betareg, expands, fpc, lpme, sBIC.

Depended on by MAP, psychomix.

Suggested by HSAUR, HSAUR2, HSAUR3, boxcoxmix, catdata, morpheus, rebmix, tlemix.

Enhanced by clue.


See at CRAN