Description
Finite Mixture Modeling for Raw and Binned Data.
Description
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'.
README.md
R package for fitting finite mixture models for both raw and binned data
Installation
For stable/pre-compiled(for Windows and OS X) version, please install from CRAN:
install.packages('mixR')
Examples
Please check the vignette.