CorReg: Linear Regression Based on Linear Structure Between Covariates

Linear regression based on a recursive structural equation model (explicit correlations) found by a MCMC algorithm. It permits to face highly correlated covariates. Variable selection is included (by lasso, elastic net, etc.). It also provides some graphical tools for basic statistics and regression trees.

Version: 1.0.5
Depends: R (≥ 3.0)
Imports: Rcpp (≥ 0.11.0), lars (≥ 1.2), Rmixmod (≥ 2.0.1), elasticnet (≥ 1.1), corrplot (≥ 0.73), Matrix (≥ 1.1), ridge (≥ 2.1), rpart (≥ 4.1-5), MASS (≥ 7.3-30), mvtnorm (≥ 0.9), mclust (≥ 4.2)
LinkingTo: Rcpp, RcppEigen
Suggests: clere (≥ 1.1), spikeslab (≥ 1.1.5), parcor (≥ 0.2), missMDA (≥ 1.7.3)
Published: 2015-06-09
Author: Clement THERY [aut, cre], Christophe BIERNACKI [ctb], Gaetan LORIDANT [ctb], Florian WATRIN [ctb], Quentin GRIMONPREZ [ctb], Vincent KUBICKI [ctb], Samuel BLANCK [ctb], Jeremie KELLNER [ctb]
Maintainer: Clement THERY <monsieur.thery at>
License: CeCILL
Copyright: ArcelorMittal
NeedsCompilation: yes
Materials: NEWS
CRAN checks: CorReg results


Reference manual: CorReg.pdf
Package source: CorReg_1.0.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-oldrel: CorReg_1.0.tgz
OS X Mavericks binaries: r-release: CorReg_1.0.5.tgz
Old sources: CorReg archive