Package: robcat 0.2

robcat: Robust Categorical Data Analysis

Robust categorical data analysis based on the theory of C-estimation developed in Welz (2024) <doi:10.48550/arXiv.2403.11954>. For now, the package only implements robust estimation of polychoric correlation as proposed in Welz, Mair and Alfons (2026) <doi:10.1017/psy.2025.10066> and robust estimation of polyserial correlation (Welz, 2026 <doi:10.1017/psy.2026.10091>) with methods for printing and plotting. We will implement further models in future releases. In addition, the package is still experimental, so input arguments and class structure may change in future releases.

Authors:Max Welz [aut, cre], Andreas Alfons [aut], Patrick Mair [aut]

robcat_0.2.tar.gz
robcat_0.2.zip(r-4.7)robcat_0.2.zip(r-4.6)robcat_0.2.zip(r-4.5)
robcat_0.2.tgz(r-4.6-x86_64)robcat_0.2.tgz(r-4.6-arm64)robcat_0.2.tgz(r-4.5-x86_64)robcat_0.2.tgz(r-4.5-arm64)
robcat_0.2.tar.gz(r-4.7-arm64)robcat_0.2.tar.gz(r-4.7-x86_64)robcat_0.2.tar.gz(r-4.6-arm64)robcat_0.2.tar.gz(r-4.6-x86_64)
robcat_0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
robcat/json (API)

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

Bug tracker:https://github.com/mwelz/robcat/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

cppquestionnairerobust-statisticscpp

3.48 score 2 stars 156 downloads 9 exports 26 dependencies

Last updated from:77ee32cc47. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK158
linux-devel-x86_64OK168
source / vignettesOK191
linux-release-arm64OK150
linux-release-x86_64OK161
macos-release-arm64OK146
macos-release-x86_64OK248
macos-oldrel-arm64OK97
macos-oldrel-x86_64OK218
windows-develOK147
windows-releaseOK139
windows-oldrelOK153
wasm-releaseOK107

Exports:initialize_parampolycorpolycor_mlepolycormatpolycormat_mlepolyserialpolyserial_efficiencypolyserial_initialize_parampolyserial_mle

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMatrixmvtnormnumDerivpracmaR6RColorBrewerRcpprlangS7scalesstringistringrvctrsviridisLitewithr