Year: 2018
Type: article
Abstract: The objective of this study was to evaluate nonlinear modeling methods to study the taper in Pinus taeda. It was used the logistic model of four parameters in both forms original and modified in the prediction of height along the trunk and the total volume of the trees. Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), standard error of estimates (Syx) and graphical analysis of the residuals were used to evaluate the models. The modified logistic model improved around 60% the standard error of the height estimates along the trunk and, consequently, the prediction of the volume reduced the prediction error by 70%. It was verified that the modified fixed logistic model showed superior fit in relation to the original logistic model.
Source: Brazilian Journal of Biometrics
Institution: Universidade do Estado de Santa Catarina
Language: English
Subfield: Forestry
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W3181467845