Finite Mixture Modeling, Clustering & Classification

Random univariate and multivariate finite mixture model generation, estimation, clustering, latent class analysis and classification. Variables can be continuous, discrete, independent or dependent and may follow normal, lognormal, Weibull, gamma, Gumbel, binomial, Poisson, Dirac, uniform or circular von Mises parametric families.


Reference manual

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install.packages("rebmix")

2.17.2 by Marko Nagode, a month ago


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


Authors: Marko Nagode [aut, cre] (ORCID: , Branislav Panic [ctb] , Jernej Klemenc [ctb] , Simon Oman [ctb]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports methods, stats, utils, graphics, grDevices


See at CRAN