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:
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