Package: CompositionalClust 1.3

Michail Tsagris

CompositionalClust: Clustering with Compositional Data

Cluster analysis with compositional data using the alpha--transformation. Relevant papers include: Tsagris M. and Kontemeniotis N. (2025). Lobachevskii Journal of Mathematics <doi:10.1134/S1995080225613700>. Tsagris M.T., Preston S. and Wood A.T.A. (2011), <doi:10.48550/arXiv.1106.1451>. Garcia-Escudero Luis A., Gordaliza Alfonso, Matran Carlos, Mayo-Iscar Agustin. (2008), <doi:10.1214/07-AOS515>.

Authors:Michail Tsagris [aut, cre], Nikolaos Kontemeniotis [aut]

CompositionalClust_1.3.tar.gz
CompositionalClust_1.3.tar.gz(r-4.7-any)CompositionalClust_1.3.tar.gz(r-4.6-any)
CompositionalClust_1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
CompositionalClust/json (API)

# Install 'CompositionalClust' in R:

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

On CRAN:

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

1.60 score 446 downloads 9 exports 167 dependencies

Last updated from:d3c6eb855d. Checks:4 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	184
source / vignettes	OK	250
linux-release-x86_64	OK	193
wasm-release	OK	233

Exports:alfa alfa.cikmeans alfa.kmeans alfa.mix.norm bic.alfamixnorm cikmeans clust.plot index_max index_min

Dependencies:abind backports base64enc BH bigassertr bigparallelr bigstatsr bit boot broom bslib cachem car carData class cli cluster codetools colorspace commonmark Compositional corrplot cowplot cpp11 crosstalk curl dendextend Deriv digest doBy doParallel dplyr DT ellipse emmeans emplik estimability evaluate factoextra FactoMineR farver fastmap ff flashClust flock fontawesome foreach forecast Formula fracdiff fs generics ggplot2 ggpubr ggrepel ggsci ggsignif ggtext glmnet glue gridExtra gridtext gtable highr htmltools htmlwidgets irlba isoband iterators jpeg jquerylib jsonlite knitr labeling later lattice lazyeval leaps lifecycle litedown lme4 lmtest lowmemtkmeans magrittr markdown MASS Matrix MatrixModels mda memoise mgcv mime minpack.lm minqa mixture mnormt modelr multcompView mvtnorm nlme nloptr nnet numDeriv osqp otel parallelly pbkrtest pillar pkgconfig png polynom promises ps purrr quadprog quantreg R6 rangen rappdirs rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen RcppGSL RcppParallel Rdpack reformulas Rfast Rfast2 rgl RhpcBLASctl rlang rmarkdown rmio Rnanoflann RSpectra rstatix S7 sass scales scatterplot3d shape showtext showtextdb sn SparseM stringi stringr survival sysfonts tibble tidyr tidyselect timeDate tinytex urca utf8 vctrs viridis viridisLite withr xfun xml2 yaml zigg zoo

Help page	Topics
Clustering with Compositional Data	CompositionalClust-package
Cluster indices for the K-means algorithm for compositional data using the alpha-transformation	alfa.cikmeans
The K-means algorithm for compositional data using the alpha-transformation	alfa.kmeans
The K-means algorithm with cluster indices computed	cikmeans
Visualization of the K-means algorithm results	clust.plot
Gaussian mixture models for compositional data using the alpha-transformation	alfa.mix.norm
Cluster indices (maximal valued) for the K-means algorithm	index_max
Cluster indices (minimial valued) for the K-means algorithm	index_min
Mixture model selection with the alpha-transformation using BIC	bic.alfamixnorm
The alpha-transformation	alfa

Package: CompositionalClust 1.3

CompositionalClust: Clustering with Compositional Data

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Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)