rpc: Ridge Partial Correlation
Computes the ridge partial correlation
coefficients in a high or ultra-high dimensional linear regression
problem. An extended Bayesian information criterion is also
implemented for variable selection. Users provide the matrix
of covariates as a usual dense matrix or a sparse matrix
stored in a compressed sparse column format. Detail of the method
is given in the manual.
| Version: |
2.0.3 |
| Imports: |
Rcpp (≥ 1.0.11), Matrix |
| LinkingTo: |
Rcpp |
| Suggests: |
MatrixExtra |
| Published: |
2025-03-22 |
| DOI: |
10.32614/CRAN.package.rpc |
| Author: |
Somak Dutta [aut, cre, cph],
An Nguyen [aut, ctb],
Run Wang [ctb],
Vivekananda Roy [ctb] |
| Maintainer: |
Somak Dutta <somakd at iastate.edu> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| CRAN checks: |
rpc results |
Documentation:
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