Table 4:

Coefficients of selected features and test mean squared prediction error for a prostate data (with p = 36 main effects and two-way interactions)

Variable	BAR	Lasso	SCAD	MCP	Adaptive Lasso	Elastic Net
lcavol	0.573	0.560	0.637	0.627	0.594	0.264
lweight					0.020	0.056
Age		−0.028	−0.073	−0.149	−0.077	−0.053
lbph						0.070
svi		0.125	0.422	0.440	0.141	0.090
lcp						0.001
gleason						0.013
(lcavol)×(lweight)						0.068
(lcavol)×(age)						0.036
(lcavol)×(svi)	0.341	0.216			0.233	0.150
(lcavol)×(gleason)						0.196
(lweight)×(gleason)	0.315	0.238	0.243	0.305	0.259	0.171
(age)×(lbph)		0.184	0.277	0.282	0.194	0.098
(age)×(svi)						0.045
(lbph)×(gleason)						0.021
(svi)×(gleason)		0.030				0.090
(lcp)×(pgg45)			−0.019	−0.067
Tuning	ξn = 44.45	λ = 0.08	γ = 3.7	γ = 3	ξ = 1.16	λ1 = 0.06
Parameters	λn = 0.1		λ = 0.08	λ = 0.07	λ = 0.21	λ2 = 0.1
Number of Selected Features	3	7	6	6	7	16
Test Error	0.461	0.484	0.587	0.583	0.513	0.498