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.


Reference manual

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2.3-17 by Bettina Gruen, a year 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 Mercator, RobMixReg, betareg, distributionsrd, expands, fmerPack, fpc, lpme, sBIC, starvz.

Depended on by MAP, flexmixNL, psychomix.

Suggested by HSAUR, HSAUR2, HSAUR3, boxcoxmix, catdata, latrend, morpheus, movMF, plotmm, tlemix.

Enhanced by clue.

See at CRAN