Table 1.

Comparison of statistics criteria of the random regression model with five covariance functions of semen traits in Thai native roosters.

Trait	Model	MSE	R 2	−2logL	AIC	${\mathbf{\rho }}_{{\mathbf{y}}_{\mathbf{i}},\widehat{{\mathbf{y}}_{\mathbf{i}}}}$	h2
Mass movement	LG2	9.862	0.505	19	21	0.750	0.115
	SP4	10.357	0.499	25	27	0.742	0.114
	SP5	9.762	0.527	12	15	0.765	0.115
	SP6	9.350	0.555	8	9	0.825	0.117
	SP8	9.346	0.559	0	0	0.842	0.118
Semen volume	LG2	8.232	0.308	19	21	0.790	0.233
	SP4	8.526	0.288	25	27	0.782	0.230
	SP5	7.822	0.332	12	15	0.792	0.232
	SP6	7.217	0.343	8	9	0.826	0.236
	SP8	7.209	0.347	0	0	0.844	0.238
Sperm concentration	LG2	10.152	0.334	19	21	0.782	0.130
	SP4	11.029	0.325	25	27	0.777	0.121
	SP5	9.753	0.340	12	15	0.799	0.130
	SP6	9.450	0.355	8	9	0.815	0.133
	SP8	9.430	0.362	0	0	0.834	0.133

LG2 = second-order Legendre polynomial function; SP4, SP5, SP6, and SP8 = linear spline functions at 4, 5, 6, and 8 knots; MSE = mean square error; R² = the coefficient of determination; −2logL = twice the negative log-likelihood; AIC = Akaike’s information criterion; ${\mathsf{\rho }}_{{\mathrm{y}}_{\mathrm{i}},\widehat{{\mathrm{y}}_{\mathrm{i}}}}$ = the predictive ability; h² = heritability.