Package: spcr 2.1.1

Shuichi Kawano

spcr: Sparse Principal Component Regression

The sparse principal component regression is computed. The regularization parameters are optimized by cross-validation.

Authors:Shuichi Kawano

spcr_2.1.1.tar.gz
spcr_2.1.1.zip(r-4.7-x86_64)spcr_2.1.1.zip(r-4.7-arm64)spcr_2.1.1.zip(r-4.6-x86_64)spcr_2.1.1.zip(r-4.6-arm64)
spcr_2.1.1.tar.gz(r-4.7-arm64)spcr_2.1.1.tar.gz(r-4.7-x86_64)spcr_2.1.1.tar.gz(r-4.6-arm64)spcr_2.1.1.tar.gz(r-4.6-x86_64)
spcr_2.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
spcr/json (API)

# Install 'spcr' in R:
install.packages('spcr', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblas

1.00 score 1 stars 4 scripts 269 downloads 1 mentions 4 exports 0 dependencies

Last updated from:c2d0890a4b. Checks:10 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK108
linux-devel-x86_64OK87
source / vignettesOK126
linux-release-arm64OK104
linux-release-x86_64OK127
windows-devel-arm64OK158
windows-devel-x86_64OK115
windows-release-arm64OK185
windows-release-x86_64OK102
wasm-releaseOK65

Exports:cv.spcrcv.spcrglmspcrspcrglm

Dependencies: