Package: rpc 2.0.3

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.

Authors:Somak Dutta [aut, cre, cph], An Nguyen [aut, ctb], Run Wang [ctb], Vivekananda Roy [ctb]

rpc_2.0.3.tar.gz
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rpc_2.0.3.tgz(r-4.5-x86_64)rpc_2.0.3.tgz(r-4.5-arm64)rpc_2.0.3.tgz(r-4.4-x86_64)rpc_2.0.3.tgz(r-4.4-arm64)rpc_2.0.3.tgz(r-4.3-x86_64)rpc_2.0.3.tgz(r-4.3-arm64)
rpc_2.0.3.tar.gz(r-4.5-noble)rpc_2.0.3.tar.gz(r-4.4-noble)
rpc_2.0.3.tgz(r-4.4-emscripten)rpc_2.0.3.tgz(r-4.3-emscripten)
rpc.pdf |rpc.html✨
rpc/json (API)

# Install 'rpc' in R:
install.packages('rpc', repos = c('https://somakd.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/somakd/rpc/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

cppopenmp

2.00 score 3 exports 3 dependencies

Last updated 4 days agofrom:2fe95246a6. Checks:12 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 23 2025
R-4.5-win-x86_64OKMar 23 2025
R-4.5-mac-x86_64OKMar 23 2025
R-4.5-mac-aarch64OKMar 23 2025
R-4.5-linux-x86_64OKMar 23 2025
R-4.4-win-x86_64OKMar 23 2025
R-4.4-mac-x86_64OKMar 23 2025
R-4.4-mac-aarch64OKMar 23 2025
R-4.4-linux-x86_64OKMar 23 2025
R-4.3-win-x86_64OKMar 23 2025
R-4.3-mac-x86_64OKMar 23 2025
R-4.3-mac-aarch64OKMar 23 2025

Exports:eBICrpcXXt.compute

Dependencies:latticeMatrixRcpp