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-4.7)RGMM_2.1.0.zip(r-4.6)RGMM_2.1.0.zip(r-4.5)
RGMM_2.1.0.tgz(r-4.6-x86_64)RGMM_2.1.0.tgz(r-4.6-arm64)RGMM_2.1.0.tgz(r-4.5-x86_64)RGMM_2.1.0.tgz(r-4.5-arm64)
RGMM_2.1.0.tar.gz(r-4.7-arm64)RGMM_2.1.0.tar.gz(r-4.7-x86_64)RGMM_2.1.0.tar.gz(r-4.6-arm64)RGMM_2.1.0.tar.gz(r-4.6-x86_64)
RGMM_2.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
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 1 scripts 215 downloads 4 exports 79 dependencies

Last updated from:c3744351b1. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK163
linux-devel-x86_64OK173
source / vignettesOK225
linux-release-arm64OK166
linux-release-x86_64OK166
macos-release-arm64OK204
macos-release-x86_64OK459
macos-oldrel-arm64OK156
macos-oldrel-x86_64OK295
windows-develOK169
windows-releaseOK154
windows-oldrelOK123
wasm-releaseOK129

Exports:Gen_MMRMMplotRobMMRobVar

Dependencies:askpassbitbit64bootcellrangerclassclicliprcodetoolscpp11crayoncurldata.tabledeadwoodDescToolsdoParallele1071Exactexpmfarverforcatsforeachfsgenieclustggplot2gldgluegtablehavenhmshttrisobanditeratorsjsonlitelabelingLaplacesDemonlatticelifecyclelmommagrittrMASSMatrixmclustmimemvtnormopensslpillarpkgconfigplyrprettyunitsprogressproxyquitefastmstR6RColorBrewerRcppRcppArmadilloRcppEigenreadrreadxlrematchreshape2rlangrootSolveRSpectrarstudioapiS7scalesstringistringrsystibbletidyselecttzdbutf8vctrsviridisLitevroomwithr

Readme and manuals

Help Manual

Help pageTopics
Robust Mixture ModelRGMM-package
Gen_MMGen_MM
RMMplotRMMplot
RobMMRobMM
RobVarRobVar