Table 7. Mean and standard error of the mean squared error values for the parametric and the nonparametric methods for the F2 population with heritability h2 = 0.30.
| F2, h2 = 0.30, MSE | Additive Mean | Epistatic Mean | Additive SE | Epistatic SE |
|---|---|---|---|---|
| Least squares regression | 1.92 | 2.32 | 0.20 | 0.26 |
| Ridge regression | 1.11 | 1.48 | 0.10 | 0.13 |
| Bayesian ridge regression | 1.11 | 1.46 | 0.10 | 0.13 |
| BLUP | 1.11 | 1.42 | 0.10 | 0.12 |
| LASSO | 1.11 | 1.40 | 0.10 | 0.12 |
| Bayes LASSO | 1.11 | 1.42 | 0.11 | 0.12 |
| Bayes A | 1.10 | 1.47 | 0.10 | 0.13 |
| Bayes B | 1.10 | 1.46 | 0.10 | 0.13 |
| Bayes C | 1.10 | 1.42 | 0.10 | 0.13 |
| Bayes Cπ | 1.10 | 1.40 | 0.10 | 0.12 |
| Nadaraya-Watson estimator | 1.32 | 1.38 | 0.12 | 0.12 |
| RKHS | 1.15 | 1.39 | 0.10 | 0.12 |
| Support vector machine | 1.16 | 1.40 | 0.10 | 0.13 |
| Neural network | 1.14 | 1.41 | 0.11 | 0.12 |
Mean and standard error of the prediction accuracy values for both the additive and the epistatic cases. The first 10 methods are parametric and the last four are nonparametric. The calculations are based on 500 replicates.