doi:10.48550/arXiv.2502.17491>. In particular, it provides code to evaluate the probability distribution function for the cut-points, compute the log-likelihood, calculate the hyper-parameters for the global variance parameter, find the distribution of McFadden's coefficient-of-determination, and fit the model in 'rstan'. Please cite the paper if you use these codes.">

R2D2ordinal: Implements Pseudo-R2D2 Prior for Ordinal Regression (original) (raw)

Implements the pseudo-R2D2 prior for ordinal regression from the paper "Psuedo-R2D2 prior for high-dimensional ordinal regression" by Yanchenko (2025) <doi:10.48550/arXiv.2502.17491>. In particular, it provides code to evaluate the probability distribution function for the cut-points, compute the log-likelihood, calculate the hyper-parameters for the global variance parameter, find the distribution of McFadden's coefficient-of-determination, and fit the model in 'rstan'. Please cite the paper if you use these codes.

Version: 1.0.1
Depends: R (≥ 3.5.0)
Imports: extraDistr (≥ 1.10.0), GIGrvg (≥ 0.8), LaplacesDemon (≥ 16.1.6), methods, Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.18.1), rstantools (≥ 2.4.0)
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.3.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.18.1), StanHeaders (≥ 2.18.0)
Suggests: knitr, rmarkdown, ggplot2, dplyr
Published: 2025-03-18
DOI: 10.32614/CRAN.package.R2D2ordinal
Author: Eric Yanchenko [aut, cre]
Maintainer: Eric Yanchenko
License: MIT + file
NeedsCompilation: yes
SystemRequirements: GNU make
CRAN checks: R2D2ordinal results

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