Smooth Effects on Response Penalty for CLM R package serp version 0.2.5 Implements a regularization method for cumulative link models using the Smooth-Effect-on-Response Penalty (SERP). This method allows flexible modeling of ordinal data by enabling a smooth transition from a general cumulative link model to a simplified version of the same model. As the tuning parameter increases from zero to infinity, the subject-specific effects for each variable converge to a single global effect. The approach addresses common issues in cumulative link models, such as parameter unidentifiability and numerical instability, by maximizing a penalized log-likelihood instead of the standard non-penalized version. Fitting is performed using a modified Newton's method. Additionally, the package includes various model performance metrics and descriptive tools. For details on the implemented penalty method, see Ugba (2021) <doi:10.21105/joss.03705> and Ugba et al. (2021) <doi:10.3390/stats4030037>. Software Depends: R (>= 4.1.0) Imports: ordinal (>= 2016-12-12), crayon, stats Suggests: covr, testthat, tibble, vctrs, pkgdown, VGAM (>= 1.1-10) Ejike R. Ugba <ejike.ugba@outlook.com> Comprehensive R Archive Network (CRAN) Ejike R. Ugba [aut, cre, cph] (ORCID: <https://orcid.org/0000-0003-2572-0023>) GPL-2 2024-11-25 application/tgz https://CRAN.R-project.org/package=serp doi:10.32614/CRAN.package.serp