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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 on the method, read the PhD thesis in the link below.
Getting started
Browse package contents
Package details |
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| 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@correg.org> |
| License | CeCILL |
| Version | 1.2.14 |
| URL | http://www.correg.org http://www.theses.fr/2015LIL10060 |
| Package repository | View on R-Forge |
| Installation |
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