Table 10:

Monte Carlo value estimates for offline simulations with γ = 0.9, $\mathcal{P}$ is the LASSO penalty, and Ω is the inverse Fisher information.

n	T	Linear VL	Polynomial VL	Gaussian VL	GGQ	Observed
25	24	0.123 (0.0750)	0.123 (0.0912)	0.140 (0.0930)	0.025 (0.0301)	−0.005
	36	0.139 (0.0780)	0.110 (0.1013)	0.138 (0.0813)	0.024 (0.0344)	−0.004
	48	0.135 (0.0690)	0.110 (0.1177)	0.143 (0.0718)	0.023 (0.0282)	0.000
50	24	0.118 (0.0705)	0.124 (0.0994)	0.137 (0.0802)	0.030 (0.0287)	−0.006
	36	0.117 (0.0827)	0.123 (0.0972)	0.121 (0.0804)	0.030 (0.0292)	0.003
	48	0.128 (0.0807)	0.113 (0.1085)	0.137 (0.0921)	0.023 (0.0282)	0.000
100	24	0.131 (0.0563)	0.123 (0.1015)	0.167 (0.0472)	0.029 (0.0295)	−0.001
	36	0.132 (0.0735)	0.148 (0.0851)	0.161 (0.0670)	0.029 (0.0334)	−0.002
	48	0.149 (0.0612)	0.137 (0.1003)	0.156 (0.0687)	0.023 (0.0267)	−0.001