rebmix: 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.

Package details

AuthorMarko Nagode [aut, cre] (<>), Branislav Panic [ctb] (<>), Jernej Klemenc [ctb] (<>), Simon Oman [ctb] (<>)
MaintainerMarko Nagode <>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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rebmix documentation built on Aug. 18, 2022, 1:06 a.m.