This study compares copula regression, recently introduced in the forest biometric literature, with four benchmark regression models for computing wood volume V in forest stands given the values of diameter at breast height D and total height H, and suggests a set of statistical techniques for the accurate assessment of model performance. Two regression models deduced from the trivariate copulabased distribution of V, D, and H are tested against the classical Spurr's model and Schumacher-Hall's model based on allometric and geometric concepts, and two regression Keywords Fagus sylvatica Á Weighted regression Á Box-Cox transformation Á Copula regression Á Normal quantile transformation Á Uncertainty Communicated by G. Kändler.
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