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Table 3 Summary metrics (mean, standard deviation, minimum and maximum) for the 16 statistics across the 1000 partial datasets (each one setting a random 50% as missing phenotypes) and obtained using either the pedigree-based NRM or the SNP-based GRM

From: Semi-parametric estimates of population accuracy and bias of predictions of breeding values and future phenotypes using the LR method

Statistic Pedigree-based NRM SNP-based GRM
Mean SD Min. Max. Mean SD Min. Max.
\(h^{2}\) 0.260 0.021 0.211 0.371 0.433 0.044 0.316 0.598
\(b_{w,p}\) 0.957 0.064 0.741 1.206 0.961 0.083 0.718 1.275
\(b_{w,p}^{r}\) 0.970 0.059 0.763 1.180 0.954 0.077 0.729 1.231
\(b_{w,p}^{v}\) 0.925 0.082 0.688 1.272 0.975 0.099 0.685 1.372
\(b_{p,w}\) 0.751 0.077 0.522 1.189 0.710 0.066 0.519 0.967
\(b_{p,w}^{r}\) 1.079 0.090 0.840 1.541 0.955 0.079 0.730 1.238
\(b_{p,w}^{v}\) 0.423 0.056 0.253 0.743 0.462 0.046 0.329 0.667
\(\rho_{w,p}\) 0.751 0.024 0.665 0.809 0.823 0.013 0.772 0.864
\(\rho_{w,p}^{r}\) 0.909 0.013 0.859 0.943 0.952 0.006 0.934 0.967
\(\rho_{w,p}^{v}\) 0.550 0.035 0.425 0.637 0.668 0.021 0.584 0.736
\(r\left( {y_{r} ,\hat{u}_{r} } \right)\) 0.849 0.012 0.804 0.892 0.898 0.015 0.852 0.944
\(r\left( {y_{v} ,\hat{u}_{v} } \right)\) 0.076 0.022 0.011 0.156 0.312 0.021 0.227 0.373
\(d_{w,p}^{r}\) 2.253 0.266 1.684 3.902 2.905 0.288 2.344 4.476
\(d_{w,p}^{v}\) 3.865 0.167 3.441 4.422 6.726 0.216 5.932 7.575
\(Vd_{w,p}^{r}\) 8.303 1.988 4.585 24.081 13.798 2.977 8.839 32.127
\(Vd_{w,p}^{v}\) 23.893 2.003 19.174 30.920 73.330 4.676 57.355 91.677