Table 1.

Evaluations of model performance based on the parsimony tests and repeated k-fold cross validations (10 folds and 10 repeats) in case of optimum u and v and Radius = 20 m.

Radius	Species	Response	Model	u	v	Para	Samples	R2	logLik	AIC	BIC	RMSE	MAE
20 m	Beech	Survival	SIZE	–	–	4	38 798	0.011	−1433	2874	2908	0.078	0.012
			SIZE + DI	0.2	0	6	38 798	0.028	−1409	2830	2881	0.078	0.012
			SIZE + DI + HOI	0.5	0.8	10	38 798	0.062	−1360	2739	2825	0.078	0.012
		Growth	SIZE	–	–	2	28 845	0.180	−35 775	71 557	71 582	0.836	0.671
			SIZE + DI	1.3	0.8	4	28 845	0.244	−34 611	69 231	69 272	0.803	0.641
			SIZE + DI + HOI	1	0.8	8	28 845	0.252	−34 443	68 904	68 978	0.799	0.637
	Spruce	Survival	SIZE	–	–	4	1058	0.099	−239	486	506	0.244	0.121
			SIZE + DI	1	0.5	6	1058	0.219	−207	427	457	0.234	0.111
			SIZE + DI + HOI	0.5	0.2	10	1058	0.276	−192	405	454	0.233	0.108
		Growth	SIZE	–	–	2	692	0.181	−967	1941	1954	0.978	0.788
			SIZE + DI	0.9	1	4	692	0.345	−890	1790	1813	0.878	0.692
			SIZE + DI + HOI	1	0.9	8	692	0.361	−881	1781	1821	0.873	0.689

Optimum u and v were selected for models with the highest R-squared and likelihood (Table S1). For the parsimony tests, AIC and BIC that were two or more points less than the next best model were considered as a meaningful improvement in in-sample performance. Models with lower RMSE and MAE computed from cross validations had better out-of-sample performance. The numbers in bold indicate that HOI-inclusive models had best performance based on AIC, BIC, RMSE or MAE. Results for the Radius = 10 m and 30 m are presented in Tables S2 and S3.