c(person("Clement", "THERY", role = c("aut", "cre"),
email = "clement.thery@arcelormittal.com"),
person("Christophe", "BIERNACKI", role = "ctb"),
person("Gaetan", "LORIDANT", role = "ctb"),
person("Florian", "WATRIN", role = "ctb"),
person("Quentin", "GRIMONPREZ", role = "ctb"),
person("Vincent", "KUBICKI", role = "ctb"),
person("Samuel", "BLANCK", role = "ctb"),
person("Jeremie","KELLNER",role="ctb")
)
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]

Linear Regression Based on Linear Structure Between Covariates
c(person("Clement", "THERY", role = c("aut", "cre"),
email = "monsieur.thery@therysolutions.com"),
person("Christophe", "BIERNACKI", role = "ctb"),
person("Gaetan", "LORIDANT", role = "ctb"),
person("Florian", "WATRIN", role = "ctb"),
person("Quentin", "GRIMONPREZ", role = "ctb"),
person("Vincent", "KUBICKI", role = "ctb"),
person("Samuel", "BLANCK", role = "ctb"),
person("Jeremie","KELLNER",role="ctb")
)
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.

c(person("Clement", "THERY", role = c("aut", "cre"),
email = "corregeous@correg.org"),
person("Christophe", "BIERNACKI", role = "ctb"),
person("Gaetan", "LORIDANT", role = "ctb"),
person("Florian", "WATRIN", role = "ctb"),
person("Quentin", "GRIMONPREZ", role = "ctb"),
person("Vincent", "KUBICKI", role = "ctb"),
person("Samuel", "BLANCK", role = "ctb"),
person("Jeremie","KELLNER",role="ctb")
)
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.