Package: ManlyMix 0.1.15.1

ManlyMix: Manly Mixture Modeling and Model-Based Clustering

The utility of this package includes finite mixture modeling and model-based clustering through Manly mixture models by Zhu and Melnykov (2016) <doi:10.1016/j.csda.2016.01.015>. It also provides capabilities for forward and backward model selection procedures.

Authors:Xuwen Zhu [aut, cre], Volodymyr Melnykov [aut], Michael Hutt [ctb, cph], Stephen Moshier [ctb, cph], Rouben Rostamian [ctb, cph]

ManlyMix_0.1.15.1.tar.gz
ManlyMix_0.1.15.1.zip(r-4.7-x86_64)ManlyMix_0.1.15.1.zip(r-4.7-arm64)ManlyMix_0.1.15.1.zip(r-4.6-x86_64)ManlyMix_0.1.15.1.zip(r-4.6-arm64)ManlyMix_0.1.15.1.zip(r-4.5-x86_64)
ManlyMix_0.1.15.1.tgz(r-4.6-x86_64)ManlyMix_0.1.15.1.tgz(r-4.6-arm64)ManlyMix_0.1.15.1.tgz(r-4.5-x86_64)ManlyMix_0.1.15.1.tgz(r-4.5-arm64)
ManlyMix_0.1.15.1.tar.gz(r-4.7-arm64)ManlyMix_0.1.15.1.tar.gz(r-4.7-x86_64)ManlyMix_0.1.15.1.tar.gz(r-4.6-arm64)ManlyMix_0.1.15.1.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ManlyMix/json (API)

# Install 'ManlyMix' in R:
install.packages('ManlyMix', repos = c('https://xzhu20.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
Datasets:

On CRAN:

Conda:

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

openblas

1.95 score 2 packages 15 scripts 404 downloads 9 exports 0 dependencies

Last updated from:4fa9d7e7f7. Checks:14 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK80
linux-devel-x86_64OK87
source / vignettesOK118
linux-release-arm64OK77
linux-release-x86_64OK89
macos-release-arm64OK125
macos-release-x86_64OK233
macos-oldrel-arm64OK162
macos-oldrel-x86_64OK352
windows-devel-arm64OK315
windows-devel-x86_64OK119
windows-release-arm64OK324
windows-release-x86_64OK79
windows-oldrel-x86_64OK77
wasm-releaseFAIL71

Exports:ClassAgreeManly.EMManly.KmeansManly.modelManly.overlapManly.plotManly.selectManly.simManly.var

Dependencies: