Hi All, I am using the package 'penalized' to perform a multiple regression on a dataset of 33 samples and 9 explanatory variables. The analysis appears to have performed as outlined and I have ended up with 4 explanatory variables and their respective regression coefficients. What I am struggling to understand is where do I get the variance explained information from and how do I determine the relative importance of the 4 variables selected? It does not appear to be a part of the penalized procedure.
I submit the final call to 'penalized' with the estimated values of lambda1 and lambda2 > fitfinal <- penalized(CHAB~.,data=chabun,lambda1=356.0856,lambda2=3.458605,model = "linear",steps=1,standardize = TRUE) # nonzero coefficients: 5 > fitfinal Penalized linear regression object 10 regression coefficients of which 5 are non-zero Loglikelihood = -154.1055 L1 penalty = 4944.889 at lambda1 = 356.0856 L2 penalty = 234.7781 at lambda2 = 3.458605 > coefficients (fitfinal) (Intercept) BC POC EXP FI 4.685739e+01 2.074521e-01 1.079459e-01 -1.373058e-05 -2.295339e+00 cheers Andy -- Andrew Halford Ph.D Associate Research Scientist Marine Laboratory University of Guam Ph: +1 671 734 2948 [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.