Table 5.

Artificial data sets: measures of model fit.

	Deviance	AIC	RMSE	${\mathbf{R}}_{\mathbf{0}}^{\mathbf{2}}$
Dimension p = 4
Order
$(1,2,3,4)$	819.096	3613.377	2.519	0.7573
Minimum	${}^{\ast }$819.096	${}^{\ast }$3613.377	${}^{\ast }$2.519	0.7244
Mean	884.212	3678.493	2.606	0.7511
Maximum	942.855	3737.136	2.660	${}^{†}$0.7803
${}^{\ast }$Value obtained for the order (1,2,3,4)
${}^{†}$Value obtained for the order (2,3,1,4)
Dimension p = 5
Order
$(1,2,3,4,5)$	936.654	4660.821	3.503	0.974
Minimum	${}^{\ast }$936.654	${}^{\ast }$4660.821	${}^{\ast }$3.503	0.714
Mean	3782.414	7507.021	19.776	0.888
Maximum	8786.090	12510.256	44.131	${}^{\ast }$0.974
${}^{\ast }$Value obtained for the order (1,2,3,4,5)
Dimension p = 6
Order
$(1,2,3,4,5,6)$	1109.437	5818.742	4.144	0.977
Minimum	${}^{\ast }$1109.437	${}^{\ast }$5818.742	${}^{\ast }$4.144	0.939
Mean	1897.034	6606.098	5.492	0.960
Maximum	2847.234	7557.387	6.621	${}^{†}$0.978
${}^{\ast }$Value obtained for the order (1,2,3,4,5,6)
${}^{†}$Value obtained for the order (1,2,3,5,4,6)