Package: mixedClust 1.0.2.1

Julien Jacques

mixedClust: Co-Clustering of Mixed Type Data

Implementation of the co-clustering method for mixed type data proposed in M. Selosse, J. Jacques, C. Biernacki (2018) <https://hal.science/hal-01893457>. It consists in clustering simultaneously the rows (observations) and the columns (features) of a heterogeneous data set.

Authors:Margot Selosse [aut], Julien Jacques [aut, cre], Christophe Biernacki [aut]

mixedClust_1.0.2.1.tar.gz
mixedClust_1.0.2.1.tar.gz(r-4.7-arm64)mixedClust_1.0.2.1.tar.gz(r-4.7-x86_64)mixedClust_1.0.2.1.tar.gz(r-4.6-arm64)mixedClust_1.0.2.1.tar.gz(r-4.6-x86_64)
mixedClust_1.0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
mixedClust/json (API)

# Install 'mixedClust' in R:
install.packages('mixedClust', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • M1 - Matrix of simulated ordinal data

On CRAN:

Conda:

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

openblascpp

2.00 score 1 stars 2 scripts 127 downloads 1 exports 45 dependencies

Last updated from:bd3dd56adc. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK217
linux-devel-x86_64OK178
source / vignettesOK306
linux-release-arm64OK202
linux-release-x86_64OK203
wasm-releaseOK174

Exports:mixedCoclust

Dependencies:ashbitopscliclustercolorspacecpp11deSolvefarverfdafdsFNNggplot2gluegtablehdrcdeisobandkernlabKernSmoothkslabelinglatticelifecyclelocfitMASSMatrixmclustmgcvmulticoolmvtnormnlmepcaPPpracmaR6rainbowRColorBrewerRcppRcppArmadilloRcppProgressRCurlrlangS7scalesvctrsviridisLitewithr

mixedClust

Rendered frommixedClustLite.Rmdusingknitr::rmarkdownon Jun 17 2026.

Last update: 2019-09-04
Started: 2019-09-04