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spcr  

Sparse Principal Component Regression
View on CRAN: Click here


Download and install spcr package within the R console
Install from CRAN:
install.packages("spcr")

Install from Github:
library("remotes")
install_github("cran/spcr")

Install by package version:
library("remotes")
install_version("spcr", "2.1.1")



Attach the package and use:
library("spcr")
Maintained by
Shuichi Kawano
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-04-01
Latest Update: 2022-10-16
Description:
The sparse principal component regression is computed. The regularization parameters are optimized by cross-validation.
How to cite:
Shuichi Kawano (2014). spcr: Sparse Principal Component Regression. R package version 2.1.1, https://cran.r-project.org/web/packages/spcr. Accessed 31 Aug. 2026.
Previous versions and publish date:
(2026-07-09 07:07), 1.0 (2014-04-01 09:17), 1.1 (2014-04-18 08:35), 1.2.1 (2014-12-04 09:05), 1.2 (2014-06-17 15:44), 2.0 (2016-10-03 13:30), 2.1 (2021-09-28 13:30)
Other packages that cited spcr R package
View spcr citation profile
Other R packages that spcr depends, imports, suggests or enhances
Complete documentation for spcr
Functions, R codes and Examples using the spcr R package
Some associated functions: cv.spcr . cv.spcrglm . spcr . spcrglm . 
Some associated R codes: SPCRLoG.R . SPCRMultiLoG.R . SPCRPoi.R . cv.spcr.R . cv.spcrglm.R . ini.lambda.R . softthresh.R . spcr.R . spcrglm.R .  Full spcr package functions and examples
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