This package is considered a duplicate. The official version of this package is found at:https://vjoshy.r-universe.dev/regMR

Package: regMR 1.0.0

Cameron Bechthold

regMR: Regularized Finite Mixture Regression Models Using MM Algorithm

Provides a comprehensive framework for fitting regularized finite mixture regression models via an MM algorithm. The sparse group lasso (sgl) penalty is applied to parameter updates within the MM algorithm for variable selection with respect to groups and covariates. The package provides multiple functions for estimation and allows users to fit models over different lambda-alpha sgl penalties and group counts.

Authors:Cameron Bechthold [aut, cre, cph], Vinay Joshy [aut, ctb, cph], Zeny Feng [aut, ths, cph], Grace Stelter [ctb]

regMR_1.0.0.tar.gz
regMR_1.0.0.zip(r-4.7-x86_64)regMR_1.0.0.zip(r-4.7-arm64)regMR_1.0.0.zip(r-4.6-x86_64)regMR_1.0.0.zip(r-4.6-arm64)
regMR_1.0.0.tar.gz(r-4.7-arm64)regMR_1.0.0.tar.gz(r-4.7-x86_64)regMR_1.0.0.tar.gz(r-4.6-arm64)regMR_1.0.0.tar.gz(r-4.6-x86_64)
regMR_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
regMR/json (API)

# Install 'regMR' in R:

install.packages('regMR', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/vjoshy/regmr/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

On CRAN:

openblas cpp openmp

1.70 score 5 scripts 349 downloads 4 exports 74 dependencies

Last updated from:7863c7c509. Checks:10 OK. Indexed: no.

Target	Result	Time
linux-devel-arm64	OK	159
linux-devel-x86_64	OK	187
source / vignettes	OK	241
linux-release-arm64	OK	179
linux-release-x86_64	OK	184
windows-devel-arm64	OK	263
windows-devel-x86_64	OK	263
windows-release-arm64	OK	287
windows-release-x86_64	OK	203
wasm-release	OK	121

Exports:FMRM MM MM_Grid plot2

Dependencies:askpass base64enc bslib cachem cli codetools cpp11 crosstalk curl data.table digest dplyr evaluate farver fastmap fontawesome fs furrr future generics ggplot2 globals glue gtable highr htmltools htmlwidgets httr isoband jquerylib jsonlite knitr labeling later lazyeval lifecycle listenv magrittr mclust memoise mime openssl otel parallelly pillar pkgconfig plotly plyr promises purrr R6 rappdirs RColorBrewer Rcpp RcppArmadillo reshape2 rlang rmarkdown S7 sass scales stringi stringr sys tibble tidyr tidyselect tinytex utf8 vctrs viridisLite withr xfun yaml

Help page	Topics
Regularized Finite Mixture Regression Model Using MM Algorithm	FMRM
Majorization-Minimization Algorithm for Finite Mixture Regression Models	MM
Majorization-Minimization Algorithm over Lambda-Alpha Grid for Finite Mixture Regression Models	MM_Grid
Plot Method for a Finite Mixture Regression Model of Class FMRM	plot.FMRM
Plot Covariates of X Against Response With Group Assignments	plot2
Print Method for a Finite Mixture Regression Model of Class FMRM	print.FMRM
Summary Method for a Finite Mixture Regression Model of Class FMRM	summary.FMRM

Package: regMR 1.0.0

regMR: Regularized Finite Mixture Regression Models Using MM Algorithm

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)