CorReg: Linear Regression Based on Linear Structure Between Covariates

Linear regression based on a recursive structural equation model (explicit multiples 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 (Boxplot with confidence intervals, etc) and regression trees.

Version: 1.1.1
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
Published: 2015-12-09
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 <corregeous at>
License: CeCILL
Copyright: ArcelorMittal
NeedsCompilation: yes
Materials: NEWS
CRAN checks: CorReg results


Reference manual: CorReg.pdf
Package source: CorReg_1.1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Mavericks binaries: r-release: CorReg_1.1.1.tgz, r-oldrel: CorReg_1.1.1.tgz
Old sources: CorReg archive


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