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CRAN: Package serp

serp: Smooth Effects on Response Penalty for CLM

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>.

Version: 0.2.5 Depends: R (≥ 4.1.0) Imports: ordinal (≥ 2016-12-12), crayon, stats Suggests: covr, testthat, tibble, vctrs, pkgdown, VGAM (≥ 1.1-10) Published: 2024-11-25 DOI: 10.32614/CRAN.package.serp Author: Ejike R. Ugba [aut, cre, cph] Maintainer: Ejike R. Ugba <ejike.ugba at outlook.com> BugReports: https://github.com/ejikeugba/serp/issues License: GPL-2 URL: https://github.com/ejikeugba/serp NeedsCompilation: no Materials: README, NEWS CRAN checks: serp results Documentation: Downloads: Reverse dependencies: Linking:

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