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care  

High-Dimensional Regression and CAR Score Variable Selection
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("care", "1.1.11")



Attach the package and use:
library("care")
Maintained by
Korbinian Strimmer
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All associated links for this package
First Published: 2010-08-08
Latest Update: 2021-11-21
Description:
Implements the regression approach of Zuber and Strimmer (2011) "High-dimensional regression and variable selection using CAR scores" SAGMB 10: 34, . CAR scores measure the correlation between the response and the Mahalanobis-decorrelated predictors. The squared CAR score is a natural measure of variable importance and provides a canonical ordering of variables. This package provides functions for estimating CAR scores, for variable selection using CAR scores, and for estimating corresponding regression coefficients. Both shrinkage as well as empirical estimators are available.
How to cite:
Korbinian Strimmer (2010). care: High-Dimensional Regression and CAR Score Variable Selection. R package version 1.1.11, https://cran.r-project.org/web/packages/care. Accessed 13 Mar. 2026.
Previous versions and publish date:
1.0.0 (2010-08-08 20:54), 1.1.0 (2011-07-23 15:50), 1.1.1 (2011-07-25 07:06), 1.1.2 (2012-01-22 09:05), 1.1.3 (2013-09-15 09:51), 1.1.4 (2014-04-19 01:11), 1.1.5 (2014-07-28 17:46), 1.1.6 (2014-11-17 00:48), 1.1.7 (2014-11-23 23:36), 1.1.8 (2015-03-09 20:38), 1.1.9 (2015-07-08 16:28), 1.1.10 (2017-03-29 19:43)
Other packages that cited care R package
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Other R packages that care depends, imports, suggests or enhances
Complete documentation for care
Functions, R codes and Examples using the care R package
Some associated functions: care-internal . care.package . carscore . efron2004 . lu2004 . slm . 
Some associated R codes: carscore.R . predict.slm.R . slm.R .  Full care package functions and examples
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