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 |
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