c(person("Bettina", "Gruen", role = c("aut", "cre"),
                    email = "Bettina.Gruen@jku.at"),
             person("Friedrich", "Leisch", role = "aut"),
             person("Deepayan", "Sarkar", role = "ctb"),
	     person("Frederic", "Mortier", rol = "ctb"),
	     person("Nicolas", "Picard", rol = "ctb"))
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.
grid, methods, modeltools (>= 0.2-16), nnet, stats, stats4
codetools, diptest, ellipse, gclus, glmnet, lme4 (>= 1.0),
MASS, mgcv (>= 1.8-0), mlbench, mlogit, multcomp, mvtnorm,
survival
Bettina Gruen [aut, cre],
  Friedrich Leisch [aut],
  Deepayan Sarkar [ctb],
  Frederic Mortier [ctb],
  Nicolas Picard [ctb]