High-Dimensional Regression and CAR Score Variable Selection
The "care" package implements the CAR regression approach
described in Zuber and Strimmer (2011).  CAR scores measure the
correlations 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 - see Zuber and Strimmer (2011)
for details. 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.

The "care" package 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.

Implements the regression approach
of Zuber and Strimmer (2011) "High-dimensional regression and variable
selection using CAR scores" SAGMB 10: 34, <DOI:10.2202/1544-6115.1730>.
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.

The "care" package 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.