mixR: 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'.

Version: 0.2.0
Depends: R (≥ 3.5.0)
Imports: ggplot2 (≥ 3.3.3), graphics, Rcpp (≥ 1.0.6), stats
LinkingTo: Rcpp
Suggests: rmarkdown, knitr, testthat (≥ 3.0.0), mockery
Published: 2021-06-01
DOI: 10.32614/CRAN.package.mixR
Author: Youjiao Yu [aut, cre]
Maintainer: Youjiao Yu <jiaoisjiao at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README NEWS
In views: Cluster
CRAN checks: mixR results


Reference manual: mixR.pdf
Vignettes: An Introduction to mixR


Package source: mixR_0.2.0.tar.gz
Windows binaries: r-devel: mixR_0.2.0.zip, r-release: mixR_0.2.0.zip, r-oldrel: mixR_0.2.0.zip
macOS binaries: r-release (arm64): mixR_0.2.0.tgz, r-oldrel (arm64): mixR_0.2.0.tgz, r-release (x86_64): mixR_0.2.0.tgz, r-oldrel (x86_64): mixR_0.2.0.tgz
Old sources: mixR archive

Reverse dependencies:

Reverse imports: cylcop


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