CorReg: Linear Regression Based on Linear Structure Between Variables

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

Version: 1.2.1
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), rpart (≥ 4.1-5), glmnet (≥ 2.0-2), MASS (≥ 7.3-30), mvtnorm (≥ 0.9), mclust (≥ 4.2), methods, graphics, grDevices, utils, stats
LinkingTo: Rcpp, RcppEigen
Suggests: clere (≥ 1.1.2), spikeslab (≥ 1.1.5), parcor (≥ 0.2), missMDA (≥ 1.7.3), tuneR, knitr, rmarkdown
Published: 2017-05-03
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 <corregeous at>
License: CeCILL
Copyright: ArcelorMittal
NeedsCompilation: yes
Citation: CorReg citation info
Materials: NEWS
CRAN checks: CorReg results


Reference manual: CorReg.pdf
Vignettes: How to take advantage of CorReg ?
Package source: CorReg_1.2.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: CorReg_1.2.1.tgz
OS X Mavericks binaries: r-oldrel: CorReg_1.2.1.tgz
Old sources: CorReg archive


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