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

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