Table 2.

Mean accuracy and standard error of the mean of each method, calculated over ten replicates each, times 100

Scenario	GBLUP	BayesB	NetSparse	GBLUP-AD	BayesB-AD	GBLUP-ADAA
Base	$63.6\pm 1.2$	$63.8\pm 1.2$	$64.8\pm 1.4$	$62.5\pm 1.3$	$61.5\pm 1.5$	$62.2\pm 1.4$
$S_{10}$	$63.6\pm 1.5$	$84.6\pm 1.5$	$91.3\pm 1.3$	$63.1\pm 1.3$	$82.0\pm 1.4$	$62.7\pm 1.4$
$S_{100}$	$61.6\pm 0.7$	$64.4\pm 1.0$	$66.8\pm 1.3$	$61.0\pm 0.6$	$61.5\pm 1.1$	$60.7\pm 0.7$
$S_{1000}$	$66.0\pm 1.8$	$64.9\pm 1.7$	$66.0\pm 1.8$	$65.7\pm 1.8$	$62.9\pm 2.1$	$65.5\pm 1.8$
$D_{\text{medium}}$	$55.4\pm 2.0$	$55.6\pm 1.8$	$56.2\pm 2.1$	$56.1\pm 2.0$	$55.4\pm 2.2$	$55.8\pm 2.0$
$D_{\text{extreme}}$	$42.8\pm 1.7$	$42.8\pm 1.5$	$43.4\pm 1.8$	$49.7\pm 1.7$	$49.5\pm 1.7$	$49.2\pm 1.7$
$E_A$	$43.9\pm 2.0$	$44.0\pm 1.8$	$44.6\pm 2.1$	$43.2\pm 2.2$	$41.4\pm 2.0$	$43.3\pm 2.4$
$E_C$	$44.9\pm 2.1$	$44.5\pm 2.4$	$45.4\pm 2.4$	$44.5\pm 2.1$	$43.9\pm 2.4$	$44.4\pm 2.2$
$E_I$	$56.5\pm 1.5$	$56.4\pm 1.7$	$58.0\pm 1.6$	$55.2\pm 1.5$	$54.0\pm 1.8$	$55.2\pm 1.5$

Each row corresponds to a scenario, as summarized in Table 1. The different columns correspond to different methods, GBLUP and Bayes-B are additive methods, GBLUP-AD and BayesB-AD are methods with additive and dominance features and GBLUP-ADAA has additive, dominance and additive × additive features