c(person("Bettina", "Gruen", role = c("aut", "cre"),
                    email = "Bettina.Gruen@R-project.org",
	            comment = c(ORCID = "0000-0001-7265-4773")),
             person("Friedrich", "Leisch", role = "aut",
	     	    comment = c(ORCID = "0000-0001-7278-1983")),
             person("Deepayan", "Sarkar", role = "ctb",
	            comment = c(ORCID = "0000-0003-4107-1553")),
	     person("Frederic", "Mortier", role = "ctb"),
	     person("Nicolas", "Picard", role = "ctb",
	            comment = c(ORCID = "0000-0001-5548-9171")))
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.
graphics, grid, grDevices, methods, modeltools (>= 0.2-16),
nnet, stats, stats4, utils
actuar, codetools, diptest, Ecdat, ellipse, gclus, glmnet,
lme4 (>= 1.1), MASS, mgcv (>= 1.8-0), mlbench, multcomp,
mvtnorm, SuppDists, survival
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>)