Table 6. The Simulation results of Example 4.4. Mean squared error (MSE) of estimates, model error (ME), mean of the number of selected covariates (NONZERO), prediction model errors (PE), mean prediction squared errors (MPSE), mean number of the false positives (FP) and false negatives (FN), the number of selected covariates among identical covariates in the model ($I_1$) and the probability of correctly eliminated identical covariates (prob).

Scenario	Method	ME	MSE	PE	MPSE	NONZERO	FP	FN	$I_1$	prob
	MLOG	0.2448	0.0005	1.0077	0.4732	49.29	0.68	0.39
(a)	ENET	3.2564	5.1164	4.0410	6.0826	45.15	18.83	22.68
	LASSO	5.1726	6.9262	5.2391	7.2317	27.86	10.45	31.61
	MLOG	0.2491	0.0009	1.1881	0.0632	49.17	0.63	0.46
(b)	ENET	5.9036	7.5343	6.4448	7.8515	57.42	26.43	18.01
	LASSO	7.1262	7.7524	7.2141	8.4866	35.17	12.98	26.81
	MLOG	0.2455	0.0017	0.9168	0.9205	25.76	0.82	0.06	48.76	0.88
(c)	ENET	3.1427	3.6126	3.9263	3.9810	32.74	11.39	3.65	36.99	0.00
	LASSO	3.6124	4.1524	3.9787	4.0974	31.41	10.62	4.21	48.14	0.65