Package: RGMM 2.1.0

RGMM: Robust Mixture Model

Algorithms for estimating robustly the parameters of a Gaussian, Student, or Laplace Mixture Model.

Authors:Antoine Godichon-Baggioni [aut, cre, cph], Stéphane Robin [aut]

RGMM_2.1.0.tar.gz
RGMM_2.1.0.zip(r-4.5)RGMM_2.1.0.zip(r-4.4)RGMM_2.1.0.zip(r-4.3)
RGMM_2.1.0.tgz(r-4.5-x86_64)RGMM_2.1.0.tgz(r-4.5-arm64)RGMM_2.1.0.tgz(r-4.4-x86_64)RGMM_2.1.0.tgz(r-4.4-arm64)RGMM_2.1.0.tgz(r-4.3-x86_64)RGMM_2.1.0.tgz(r-4.3-arm64)
RGMM_2.1.0.tar.gz(r-4.5-noble)RGMM_2.1.0.tar.gz(r-4.4-noble)
RGMM_2.1.0.tgz(r-4.4-emscripten)RGMM_2.1.0.tgz(r-4.3-emscripten)
RGMM.pdf |RGMM.html
RGMM/json (API)

# Install 'RGMM' in R:
install.packages('RGMM', repos = c('https://godichon-baggioni.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

1.00 score 178 downloads 4 exports 80 dependencies

Last updated 1 years agofrom:c3744351b1. Checks:11 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 02 2025
R-4.5-win-x86_64OKMar 02 2025
R-4.5-mac-x86_64OKMar 02 2025
R-4.5-mac-aarch64OKMar 02 2025
R-4.5-linux-x86_64OKMar 02 2025
R-4.4-win-x86_64OKMar 02 2025
R-4.4-mac-x86_64OKMar 02 2025
R-4.4-mac-aarch64OKMar 02 2025
R-4.3-win-x86_64OKMar 02 2025
R-4.3-mac-x86_64OKMar 02 2025
R-4.3-mac-aarch64OKMar 02 2025

Exports:Gen_MMRMMplotRobMMRobVar

Dependencies:askpassbitbit64bootcellrangerclassclicliprcodetoolscolorspacecpp11crayoncurldata.tableDescToolsdoParallele1071Exactexpmfansifarverforcatsforeachgenieclustggplot2gldgluegtablehavenhmshttrisobanditeratorsjsonlitelabelingLaplacesDemonlatticelifecyclelmommagrittrMASSMatrixmclustmgcvmimemunsellmvtnormnlmeopensslpillarpkgconfigplyrprettyunitsprogressproxyR6RColorBrewerRcppRcppArmadilloRcppEigenreadrreadxlrematchreshape2rlangrootSolveRSpectrarstudioapiscalesstringistringrsystibbletidyselecttzdbutf8vctrsviridisLitevroomwithr

Readme and manuals

Help Manual

Help pageTopics
Robust Mixture ModelRGMM-package
Gen_MMGen_MM
RMMplotRMMplot
RobMMRobMM
RobVarRobVar