Allometric equations to predict the total above-ground biomass of radiata pine trees

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Table II

Parameter estimates, their standard errors and goodness of fit statistics for the models developed to predict total above ground biomass. Values of root mean square error (RMSE) and the Akaike information criterion (AIC) can only be used for comparisons with the same class of model (i.e. logarithmic transformed models or weighted arithmetic models).

Equation No.	Parameter estimates					RMSE	AIC	FI	R²

	β ₀	β ₁	β ₂	β ₃	β ₄
Logarithmic transformed models
3	–1.9400	2.1824	–	–	–	0.2917	323.5	13.72	0.92
	(0.3726)	(0.1236)
4	–0.5816	1.1240	0.2030	–	–	0.2332	44.8	10.97	0.95
	(0.3667)	(0.1212)	(0.0108)
5	–2.1004	1.8594	0.4370			0.2709	234.0	12.74	0.93
	(0.3672)	(0.1282)	(0.1310)
6	–0.9753	1.0241	0.1811	0.3399	–	0.2268	13.6	10.67	0.95
	(0.3375)	(0.1127)	(0.0110)	(0.1100)
7	–0.9069	1.2273	0.1411	–0.0078	0.0840	0.2266	11.4	10.66	0.95
	0.3452	0.1357	0.0221	0.2126	0.0400
8	–2.4150	0.8186	–	–	–	0.2768	246.9	13.02	0.93
	0.4170	0.0455
9	–1.1602	0.4859	0.0219	–	–	0.2383	58.2	11.20	0.95
Weighted arithmetic models
13	0.1291	2.2718	–	–	–	0.3052	5436	16.39	0.88
	0.0080	0.0435
14	0.1039	0.8229	–	–	–	0.2409	5406	16.12	0.94
	(0.0113)	(0.0071)
15	0.0944	1.5286	–	–	–	0.2433	5458	16.76	0.95
	(0.0111)	(0.0214)
16	0.0994	0.4206				0.2694	5347	15.38	0.95
	(0.0101)	(0.0213)
17	0.0977	2.0362	0.3845	–	–	0.2734	5349	15.38	0.95
	(0.0100)	(0.0472)	(0.0555)
18	69.4057	0.2877	–	–	–	0.1007	5721	19.59	0.78
	(45.5534)	(0.0053)
19	2.0597	0.0185	–	–	–	0.2190	5571	18.18	0.94
	(0.9392)	(0.0010)
20	0.7013	0.0807	–	–	–	0.1620	5237	13.97	0.97
	(0.3527)	(0.0057)