spcr: Sparse Principal Component Regression

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

Author
Shuichi Kawano
Date of publication
2016-10-03 13:30:02
Maintainer
Shuichi Kawano <skawano@uec.ac.jp>
License
GPL (>= 2)
Version
2.0
URLs

View on CRAN

Man pages

cv.spcr
Cross-validation for spcr
cv.spcrglm
Cross-validation for spcr-glm
spcr
Fit a sparse principal component regression (SPCR)
spcrglm
Fit a sparse principal component regression for generalized...

Files in this package

spcr
spcr/src
spcr/src/Makevars
spcr/src/SPCR.c
spcr/NAMESPACE
spcr/R
spcr/R/spcr.R
spcr/R/SPCRPoi.R
spcr/R/cv.spcrglm.R
spcr/R/SPCRLoG.R
spcr/R/spcrglm.R
spcr/R/SPCRMultiLoG.R
spcr/R/ini.lambda.R
spcr/R/softthresh.R
spcr/R/cv.spcr.R
spcr/MD5
spcr/DESCRIPTION
spcr/man
spcr/man/cv.spcr.Rd
spcr/man/spcrglm.Rd
spcr/man/cv.spcrglm.Rd
spcr/man/spcr.Rd