Table 2.
Comparison of prediction performance between AR-LSBP, GP-LSBP and ind-LSBP.
| Nmiss | Average log-likelihood | |||||
| AR-LSBP | GP-LSBP | ind-LSBP | ||||
| VB | MCMC | VB | MCMC | VB | MCMC | |
| 1 | −3.948 | −1.975 | −4.102 | −2.123 | −21.194 | −2.641 |
| 2 | −4.211 | −2.241 | −4.526 | −2.473 | −27.195 | −3.077 |
| 3 | −4.468 | −2.573 | −4.718 | −2.652 | −27.776 | −3.507 |
| 4 | −4.882 | −2.740 | −5.133 | −3.108 | −26.682 | −3.963 |
| 5 | −5.801 | −3.014 | −5.987 | −3.521 | −31.217 | −4.316 |
| Nmiss | Accuracy rate of segmentation | |||||
| AR-LSBP | GP-LSBP | ind-LSBP | ||||
| VB | MCMC | VB | MCMC | VB | MCMC | |
| 1 | 0.9792 | 0.9794 | 0.9767 | 0.9758 | 0.7165 | 0.9545 |
| 2 | 0.9787 | 0.9786 | 0.9761 | 0.9754 | 0.6669 | 0.9581 |
| 3 | 0.9787 | 0.9785 | 0.9763 | 0.9752 | 0.6458 | 0.9379 |
| 4 | 0.9780 | 0.9783 | 0.9752 | 0.9740 | 0.6647 | 0.9274 |
| 5 | 0.9763 | 0.9770 | 0.9741 | 0.9633 | 0.6131 | 0.9066 |