TABLE IV.
Simulation results for Model 5. We use Model 2 with increased dimensions p = 1000, q = 400 by adding noise variables1
| Model | Method | MSE-Est | MSE-Pred | FPR (%) | FNR (%) | Rank | Rank (%) | Orth |
|---|---|---|---|---|---|---|---|---|
| 5 | OLS | 151.5 (5.7) | 230.1 (122.9) | 100 | 0 | |||
| Lasso | 3.9 (1.8) | 29.3 (11.8) | 0.6 | 0 | ||||
| RRR | 146.8 (7.7) | 61.5 (77.1) | 100 | 0 | 2.6 | 57.7 | 0 | |
| SOFAR-L | 0.1 (0.0) | 0.1 (0.0) | 0 | 0 | 3 | 100 | 0 | |
| RSSVD | 6.6 (14.4) | 2.8 (2.7) | 3.1 | 1 | 3 | 99 | 49.1 | |
| SOFAR-GL | 0.1 (0.0) | 0.2 (0.1) | 0.8 | 0 | 3 | 100 | 0 | |
| SRRR | 0.5 (0.2) | 3.6 (1.8) | 19.7 | 0 | 3 | 100 | 55.5 |
1
Adaptive versions of Lasso, SOFAR-L, RSSVD, SOFAR-GL, and SRRR were applied. Means of performance measures with standard deviations in parentheses over 300 replicates are reported. MSE-Est values are scaled by 105 and MSE-Pred values are scaled by multiplying 103.