From: Bayesian neural networks with variable selection for prediction of genotypic values
Scenario | GBLUP | BayesB | GBLUP-AD | BayesB-AD | GBLUP-ADAA |
---|---|---|---|---|---|
Base | \(3.21\times 10^{-2}\) | \(3.98\times 10^{-2}\) | \(4.52\times 10^{-3}\) | \(1.92\times 10^{-4}\) | \(1.67\times 10^{-3}\) |
\(S_{10}\) | \(2.05\times 10^{-8}\) | \(6.96\times 10^{-6}\) | \(7.45\times 10^{-9}\) | \(9.36\times 10^{-6}\) | \(4.48\times 10^{-9}\) |
\(S_{100}\) | \(4.63\times 10^{-4}\) | \(3.64\times 10^{-3}\) | \(2.18\times 10^{-4}\) | \(2.79\times 10^{-5}\) | \(1.52\times 10^{-4}\) |
\(S_{1000}\) | \(5.00\times 10^{-1}\) | \(3.48\times 10^{-3}\) | \(1.33\times 10^{-1}\) | \(1.29\times 10^{-3}\) | \(9.67\times 10^{-2}\) |
\(D_{\text {medium}}\) | \(5.75\times 10^{-3}\) | \(1.47\times 10^{-1}\) | \(5.00\times 10^{-1}\) | \(1.19\times 10^{-1}\) | \(2.10\times 10^{-1}\) |
\(D_{\text {extreme}}\) | \(2.09\times 10^{-2}\) | \(1.72\times 10^{-1}\) | \(-1.85\times 10^{-6}\) | \(-7.57\times 10^{-6}\) | \(-5.45\times 10^{-6}\) |
\(E_A\) | \(5.75\times 10^{-3}\) | \(1.95\times 10^{-1}\) | \(1.50\times 10^{-3}\) | \(2.39\times 10^{-4}\) | \(1.14\times 10^{-2}\) |
\(E_C\) | \(8.92\times 10^{-2}\) | \(9.61\times 10^{-3}\) | \(1.98\times 10^{-1}\) | \(1.04\times 10^{-1}\) | \(1.60\times 10^{-1}\) |
\(E_I\) | \(7.92\times 10^{-3}\) | \(1.67\times 10^{-3}\) | \(4.13\times 10^{-4}\) | \(8.27\times 10^{-5}\) | \(5.27\times 10^{-4}\) |