Penalized Ordinal Regression

Fits ordinal regression models with elastic net penalty. Supported model families include cumulative probability, stopping ratio, continuation ratio, and adjacent category. These families are a subset of vector glm's which belong to a model class we call the elementwise link multinomial-ordinal (ELMO) class. Each family in this class links a vector of covariates to a vector of class probabilities. Each of these families has a parallel form, which is appropriate for ordinal response data, as well as a nonparallel form that is appropriate for an unordered categorical response, or as a more flexible model for ordinal data. The parallel model has a single set of coefficients, whereas the nonparallel model has a set of coefficients for each response category except the baseline category. It is also possible to fit a model with both parallel and nonparallel terms, which we call the semi-parallel model. The semi-parallel model has the flexibility of the nonparallel model, but the elastic net penalty shrinks it toward the parallel model. For details, refer to Wurm, Hanlon, and Rathouz (2017) .


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install.packages("ordinalNet")

2.6 by Michael Wurm, a month ago


Browse source code at https://github.com/cran/ordinalNet


Authors: Michael Wurm [aut, cre] , Paul Rathouz [aut] , Bret Hanlon [aut]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports stats, graphics

Suggests testthat, MASS, glmnet, penalized, glmnetcr, VGAM, rms


See at CRAN