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.
Package details |
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Author | Benjamin Stokell [aut], Daniel Grose [ctb, cre], Rajen Shah [ctb] |
Maintainer | Daniel Grose <dan.grose@lancaster.ac.uk> |
License | GPL (>= 2) |
Version | 2.0.3 |
Package repository | View on CRAN |
Installation |
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