Package: OrdinalCompositions 0.1.0

Nicola Piras

OrdinalCompositions: Wasserstein-Based Regression for Ordinal Compositional Data

Tools analyzing regression models for ordinal compositional data using Wasserstein-based distances. The package includes linear programming solvers under simplex constraints, tensor product constructions and performance metrics.

Authors:Nicola Piras [aut, cre], Monica Musio [aut], Beniamino Cappelletti-Montano [aut]

OrdinalCompositions_0.1.0.tar.gz
OrdinalCompositions_0.1.0.tar.gz(r-4.7-any)OrdinalCompositions_0.1.0.tar.gz(r-4.6-any)
OrdinalCompositions_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
OrdinalCompositions/json (API)

# Install 'OrdinalCompositions' in R:
install.packages('OrdinalCompositions', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

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

2.30 score 12 exports 4 dependencies

Last updated from:339461178e. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK109
source / vignettesOK239
linux-release-x86_64OK112
wasm-releaseOK107

Exports:compute_R2compute_wfrechet_meandefault_lambda_gridOCCopiordinal_regression_simplexsafe_dirichletselect_lambdasolve_simplex_lptensor_productwdwd_matrix

Dependencies:extraDistrlpSolveAPIRcppRcppArmadillo

Educational dataset example

Rendered fromeducFM_analysis.Rmdusingknitr::rmarkdownon Jun 19 2026.

Last update: 2026-06-19
Started: 2026-06-19

Satisfaction of life in own city dataset

Rendered fromCitySatisf_analysis.Rmdusingknitr::rmarkdownon Jun 19 2026.

Last update: 2026-06-19
Started: 2026-06-19