Table 1.

Comparison of mean squared prediction error (MSPE), true positive rate (TPR) and false positive rate (FPR) with standard errors (SE).

Simulation 1: n = 400, p = 40, SNR = 10				Simulation 2: n = 400, p = 40, SNR = 5
Method	MSPE (SE)	TPR (SE)	FPR (SE)	Method	MSPE (SE)	TPR (SE)	FPR (SE)
PLS	504.2 (293.8)			PLS	655.2 (212.9)
Sparse PLS	72.6 (4.1)	1.00 (0.00)	0.61 (0.27)	Sparse PLS	143.7 (9.8)	1.00 (0.00)	0.66 (0.29)
RPLS	66.4 (3.8)	1.00 (0.00)	0.22 (0.35)	RPLS	131.4 (9.3)	1.00 (0.00)	0.19 (0.37)
Lasso	70.9 (4.9)	0.60 (0.07)	0.00 (0.02)	Lasso	139.3 (9.5)	0.49 (0.07)	0.00 (0.00)
Elastic net	70.5 (4.5)	0.61 (0.07)	0.01 (0.03)	Elastic net	139.0 (9.5)	0.50 (0.07)	0.00 (0.00)

Simulation 3: n = 40, p = 80, SNR = 10				Simulation 4: n = 40, p = 80, SNR = 5
Method	MSPE (SE)	TPR (SE)	FPR (SE)	Method	MSPE (SE)	TPR (SE)	FPR (SE)
PLS	624.1 (256.5)			PLS	612.6 (256.8)
Sparse PLS	104.9 (26.3)	0.99 (0.05)	0.77 (0.30)	Sparse PLS	206.4 (53.9)	0.98 (0.07)	0.70 (0.31)
RPLS	76.0 (20.8)	1.00 (0.00)	0.45 (0.43)	RPLS	155.1 (59.0)	1.00 (0.00)	0.52 (0.43)
Lasso	83.7 (19.7)	0.17 (0.04)	0.02 (0.06)	Lasso	178.3 (49.7)	0.12 (0.04)	0.01 (0.02)
Elastic net	82.4 (18.6)	0.17 (0.03)	0.02 (0.04)	Elastic net	172.7 (46.0)	0.12 (0.04)	0.01 (0.03)

Simulation 5: n = 40, p = 200, SNR = 10				Simulation 2: n = 40, p = 200, SNR = 5
Method	MSPE (SE)	TPR (SE)	FPR (SE)	Method	MSPE (SE)	TPR (SE)	FPR (SE)
PLS	649.7 (175.8)			PLS	691.9 (188.5)
Sparse PLS	85.7 (20.4)	1.00 (0.02)	0.76 (0.32)	Sparse PLS	182.0 (42.0)	0.98 (0.08)	0.61 (0.36)
RPLS	84.8 (52.2)	1.00 (0.00)	0.53 (0.47)	RPLS	153.3 (40.9)	1.00 (0.00)	0.48 (0.49)
Lasso	83.1 (15.1)	0.19 (0.04)	0.01 (0.01)	Lasso	163.1 (35.7)	0.15 (0.04)	0.00 (0.01)
Elastic net	82.2 (14.7)	0.19 (0.05)	0.00 (0.01)	Elastic net	160.6 (33.7)	0.15 (0.03)	0.01 (0.02)