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.
remove ridge dependency by using MASS function lm.ridge Add a new BoxPlot function with confidence intervals and anova integrated
Changing random generator in C to use runif() instead.
bug removal when X was a data.frame in density_estimatione