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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