swMATH ID: 40435
Software Authors: Ejike R. Ugba
Description: R package serp: Smooth Effects on Response Penalty for ’CLM’. A regularization method for the cumulative link models. The ’smooth-effect-on-response penalty’ (’SERP’) provides flexible modelling of the ordinal model by enabling the smooth transition from the general cumulative link model to a coarser form of the same model. In other words, as the tuning parameter goes from zero to infinity, the subject-specific effects associated with each variable in the model tend to a unique global effect. The parameter estimates of the general cumulative model are mostly unidentifiable or at least only identifiable within a range of the entire parameter space. Thus, by maximizing a penalized rather than the usual non-penalized log-likelihood, this and other numerical problems common with the general model are to a large extent eliminated. Fitting is via a modified Newton’s method. Several standard model performance and descriptive methods are also available. For more details on the penalty implemented here, see, ’Ugba et al. (2021)’ <doi:10.3390/stats4030037> and Tutz and Gertheiss (2016) <doi:10.1177/1471082X16642560>.
Homepage: https://cran.r-project.org/web/packages/serp/index.html
Source Code:  https://github.com/cran/serp
Dependencies: R
Keywords: Journal of Open Source Software; serp; R; R package; smoothing; ordinal regression; cumulative link model; CLM
Related Software: pkgdown; ordinal; VGAM; R; brant; mlogitgof; stats; Mlogit; MASS (R); nnet; generalhoslem; performance; ResourceSelection; AICcmodavg; goftest; gofcat; CRAN; SAS; ordinalNet; SPSS
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