Table 1.
Bayesian variable selection with the extended stochastic gradient Langevin dynamics (eSGLD), reversible jump Metropolis-Hastings (RJMH), split-and-merge (SaM) and Bayesian Lasso (B-Lasso) algorithms, where FSR, NSR, MSE1 and MSE0 are reported in averages over 10 datasets with standard deviations given in the parentheses, and the CPU time (in minutes) was recorded for one dataset on a Linux machine with Intel® Core™i7–3770 CPU@3.40GHz.
| Algorithm | FSR | NSR | MSE1 | MSE0 | CPU(m) |
|---|---|---|---|---|---|
| eSGLD | 0(0) | 0(0) | 2.91 × 10−3(1.90 × 10−3) | 1.26 × 10−7(1.18 × 10−8) | 3.3 |
| RJMH | 0.50(0.10) | 0.16(0.042) | 1.60 × 10−1(3.89 × 10−2) | 2.64 × 10−5(8.75 × 10−6) | 180.1 |
| SaM | 0.05(0.05) | 0.013(0.013) | 1.29 × 10−2(1.27 × 10−2) | 1.01 × 10−6(1.00 × 10−6) | 150.4 |
| B-Lasso | 0(0) | 0(0) | 2.32 × 10−4(3.58 × 10−5) | 1.40 × 10−7(5.08 × 10−9) | 32.8 |