Table 2.

Performance measures for L ₀ and L ₁ regularized regression with λ = max⁡{λ _MSE, λ _SS} over 100 simulations, where values in the parenthesis are the standard deviations. # SF: number of average selected features; MSE: average mean squared error; $‖\widehat{\theta }-\theta ‖$: average absolute bias when comparing true and estimated parameters.

r	L 0			L 1
	# SF	MSE	$‖\widehat{\theta }-\theta ‖$	#SF	MSE	$‖\widehat{\theta }-\theta ‖$
0	3.09 (±0.53)	1.04 (±0.15)	0.18 (±0.11)	13.3 (±4.56)	1.21 (±0.17)	0.39 (±0.1)
0.3	3.08 (±0.54)	1.04 (±0.15)	0.17 (±0.07)	14.5 (±4.20)	1.22 (±0.17)	0.42 (±0.19)
0.6	3.10 (±0.46)	1.07 (±0.17)	0.21 (±0.10)	13.8 (±5.4)	1.27 (±0.47)	0.57 (±0.25)
0.8	3.02 (±0.14)	1.04 (±0.14)	0.26 (±0.13)	13.4 (±4.91)	1.25 (±0.21)	0.74 (±0.25)