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Table 6 Accuracy of GEBV, regression of TBV on GEBV (Slope), and bias and standard error (SE) of estimates of heritabilities (\({\hat{h}}^2\)) and genetic correlations (GC) with and without eigenvalue decomposition (EVD), based on 100 replicates of the simulation of scenario 1

From: A new approach fits multivariate genomic prediction models efficiently

Method

Accuracy

Slope

Bias of \({\hat{h}}^2\)

SE of \({\hat{h}}^2\)

Bias of GC

SE of GC

REML-EVD

0.87 (0.02)

1.00 (0.03)

− 0.01 (0.02)

0.04 (0.01)

0.00 (0.04)

0.14 (0.03)

PEGS

0.86 (0.02)

1.02 (0.03)

− 0.03 (0.04)

0.07 (0.02)

0.02 (0.08)

0.18 (0.04)

PEGS-EVD

0.86 (0.02)

1.02 (0.03)

− 0.04 (0.04)

0.07 (0.02)

0.02 (0.08)

0.18 (0.04)

THGS

0.86 (0.02)

1.02 (0.03)

− 0.03 (0.04)

0.07 (0.02)

0.01 (0.08)

0.17 (0.04)

THGS-EVD

0.87 (0.02)

1.00 (0.03)

− 0.02 (0.03)

0.05 (0.01)

0.00 (0.04)

0.13 (0.02)

UV-THGS

0.84 (0.04)

1.06 (0.09)

− 0.02 (0.05)

0.08 (0.02)

UV-THGS-EVD

0.84 (0.03)

1.03 (0.04)

− 0.03 (0.03)

0.05 (0.01)

  1. REML restricted maximum likelihood, EVD eigenvalue decomposition, PEGS pseudo expectation Gauss–Seidel, THGS tilde-hat Gauss–Seidel, UV-THGS univariate-tilde-hat Gauss–Seidel