TABLE 2.

Estimates of log Bayes factors (lBFs) for various nested model comparisons given the budding index data alone. The model indexed by an entry’s column is the larger of the models and is represented in the numerator of the lBFs in that column; the model indexed by an entry’s row is the smaller of the two. The last two rows of the table provide the average and standard deviation of the RMSE of the model’s fitted values to the observed budding index data over a sample of 1000 draws from the posterior

Submodel	Full model	μ0 = 0	δ = 0	${\sigma }_0^2=0$	μ0 = 0 δ = 0	μ0 = 0 ${\sigma }_0^2=0$	δ = 0 ${\sigma }_0^2=0$	μ0 = 0 δ = 0 ${\sigma }_0^2=0$
μ0 = 0	368.62	0.00
δ = 0	18.75		0.00
${\sigma }_0^2=0$	31.00			0.00
μ0 = δ = 0	364.22	−4.40	345.47		0.00
${\mu }_0={\sigma }_0^2=0$	363.78	−4.84		332.78		0.00
$\delta ={\sigma }_0^2=0$	31.04		12.28	0.04			0.00
${\mu }_0=\delta ={\sigma }_0^2=0$	359.37	−9.25	340.62	328.37	−4.85	−4.41	328.33	0.00
E(RMSE)	3.70	13.69	4.35	3.99	13.67	13.65	3.92	13.63
SD(RMSE)	0.16	0.10	0.19	0.15	0.10	0.09	0.14	0.09