Package: serp 0.2.5
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>.
Authors:
serp_0.2.5.tar.gz
serp_0.2.5.tar.gz(r-4.5-noble)serp_0.2.5.tar.gz(r-4.4-noble)
serp_0.2.5.tgz(r-4.4-emscripten)serp_0.2.5.tgz(r-4.3-emscripten)
serp.pdf |serp.html✨
serp/json (API)
NEWS
# Install 'serp' in R: |
install.packages('serp', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ejikeugba/serp/issues
- wine - Bitterness of wine dataset
Last updated 1 days agofrom:f115a215b1. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 25 2024 |
R-4.5-linux | OK | Nov 25 2024 |
Exports:serpserp.control
Dependencies:crayonlatticeMASSMatrixnlmenumDerivordinalucminf
Readme and manuals
Help Manual
Help page | Topics |
---|---|
AIC for a fitted serp object | AIC.serp |
ANOVA method for a fitted serp object | anova.serp |
BIC for a fitted serp object | BIC.serp |
Coefficients for a fitted serp object | coef.serp coefficients.serp |
Confidence interval for a fitted serp object | confint.serp |
Log-likelihood for a fitted serp object | logLik.serp |
Prediction from fitted serp model | predict.serp |
Print method for a fitted serp object | print.serp |
Print method for an object of class summary.serp | print.summary.serp |
Smooth Effects on Response Penalty for CLM | serp |
Control parameters for a fitted serp object | serp.control |
Summary method for a fitted serp object. | summary.serp |
Variance covariance matrix for a fitted serp object | vcov.serp |
Bitterness of wine dataset | wine |