Finite Mixture Modeling for Raw and Binned Data

Performs maximum likelihood estimation for finite mixture models for families including Normal, Weibull, Gamma and Lognormal by using EM algorithm, together with Newton-Raphson algorithm or bisection method when necessary. It also conducts mixture model selection by using information criteria or bootstrap likelihood ratio test. The data used for mixture model fitting can be raw data or binned data. The model fitting process is accelerated by using R package 'Rcpp'.




  • First version

Reference manual

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0.2.0 by Youjiao Yu, 8 months ago

Browse source code at

Authors: Youjiao Yu [aut, cre]

Documentation:   PDF Manual  

Task views: Cluster Analysis & Finite Mixture Models

GPL (>= 2) license

Imports ggplot2, graphics, Rcpp, stats

Suggests rmarkdown, knitr, testthat, mockery

Linking to Rcpp

See at CRAN