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 |
| 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 |
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