Table 4.

Average posterior inference on sire (co)variances from ten replicates using the bivariate Student's-t (BSt) and normal (BN) fitted models with different residual degrees of freedom (DF).

		Fitted Model2
		BSt			BN
True Parameters	True Model1	PM ± SE3	95% PPI4	ESS5	PM ± SE	95% PPI	ESS
= 2.0	BSt-4	2.24 ± 0.16	[1.32, 3.62]	20,983	2.31 ± 0.18	[1.30, 3.83]	20,694
	BSt-12	2.44 ± 0.14	[1.48, 3.88]	24,767	2.39 ± 0.14	[1.44, 3.81]	25,794
	BN-∞	2.49 ± 0.17	[1.52, 3.93]	26,715	2.49 ± 0.17	[1.53, 3.93]	28,154
= 1.5	BSt-4	1.41 ± 0.17	[0.40, 2.76]	23,326	1.43 ± 0.18	[0.33, 2.89]	23,146
	BSt-12	1.93 ± 0.19	[0.83, 3.47]	27,428	1.89 ± 0.19	[0.80, 3.42]	28,683
	BN-∞	1.77 ± 0.22	[0.72, 3.23]	28,441	1.77 ± 0.21	[0.71, 3.22]	30,064
= 4.0	BSt-4	4.23 ± 0.30	[2.59, 6.70]	24,192	4.33 ± 0.33	[2.57, 6.99]	23,978
	BSt-12	4.77 ± 0.29	[2.97, 7.48]	27,674	4.80 ± 0.30	[2.98, 7.55]	29,102
	BN-∞	4.46 ± 0.39	[2.79, 6.96]	29,013	4.45 ± 0.39	[2.78, 6.98]	29,365

¹Used to simulate data

²Used in analysis of simulated data

³Posterior mean ± Standard Error

⁴95% equal-tailed posterior probability interval based on the 2.5^th and 97.5^th percentiles of the posterior density

⁵Effective sample size