CatReg: Solution Paths for Linear and Logistic Regression Models with Categorical Predictors, with SCOPE Penalty

Computes solutions for linear and logistic regression models with potentially high-dimensional categorical predictors. This is done by applying a nonconvex penalty (SCOPE) and computing solutions in an efficient path-wise fashion. The scaling of the solution paths is selected automatically. Includes functionality for selecting tuning parameter lambda by k-fold cross-validation and early termination based on information criteria. Solutions are computed by cyclical block-coordinate descent, iterating an innovative dynamic programming algorithm to compute exact solutions for each block.

Getting started

Package details

AuthorBenjamin Stokell [aut], Daniel Grose [ctb, cre], Rajen Shah [ctb]
MaintainerDaniel Grose <>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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CatReg documentation built on June 14, 2021, 5:07 p.m.