Genetics Selection Evolution

Table 2 Estimated and true genetic parameters based on the GLMM for the default scenario with \({{{r}}}_{{{A}}}=0\)

From: Towards genetic improvement of social behaviours in livestock using large-scale sensor data: data simulation and genetic analysis

\({r}_{A}=0\)	\({h}_{o}^{2}\)
	0.05		0.1		0.2
	Estimated	True^a	Estimated	True^a	Estimated	True^a
\({\sigma }_{{A}_{\alpha }}^{2}\)	0.0121	0.012	0.0396	0.038	0.1719	0.170
\({\sigma }_{{A}_{\beta }}^{2}\)	0.0138	0.012	0.0375	0.038	0.1706	0.170
\({\sigma }_{{Ep}_{\alpha }}^{2}\)	0.0117	0.012	0.0358	0.038	0.1649	0.170
\({\sigma }_{{Ep}_{\beta }}^{2}\)	0.0113	0.012	0.0361	0.038	0.1655	0.170
\({r}_{A}{\sigma }_{{A}_{\alpha }}{\sigma }_{{A}_{\beta }}\)	0.0009	0	0.0012	0	– 0.0004	0

Estimates were averages of 25 replicates.
^aThe true values of variances were the simulated input values (Table 1).
\({r}_{A}{\sigma }_{{A}_{\alpha }}{\sigma }_{{A}_{\beta }}\) is the genetic covariance between the two traits.

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ISSN: 1297-9686

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