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.(Markov Chain Monte Carlo) 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. For more information about the method, read the PhD thesis of Clement Thery (2015) in the link below.

Package details

AuthorClement Thery [aut, cre], Christophe Biernacki [ths], Gaetan Loridant [ths], Florian Watrin [ctb], Quentin Grimonprez [ctb], Vincent Kubicki [ctb], Samuel Blanck [ctb], Jeremie Kellner [ctb]
MaintainerClement Thery <>
Package repositoryView on CRAN
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CorReg documentation built on Feb. 20, 2020, 5:07 p.m.