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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:

Reference manual:rpc.html ,rpc.pdf

Downloads:

Package source: rpc_2.0.3.tar.gz
Windows binaries: r-devel:rpc_2.0.3.zip, r-release:rpc_2.0.3.zip, r-oldrel:rpc_2.0.3.zip
macOS binaries: r-release (arm64):rpc_2.0.3.tgz, r-oldrel (arm64):rpc_2.0.3.tgz, r-release (x86_64):rpc_2.0.3.tgz, r-oldrel (x86_64):rpc_2.0.3.tgz

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=rpcto link to this page.


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