MODELING THE GROWTH OF Eucalyptus CLONES USING THE CHAPMAN-RICHARDS MODEL WITH DIFFERENT SYMMETRICAL ERROR DISTRIBUTIONS

• Autor(a) principal: Filho, Luiz Medeiros de Araujo Lima
• Data de Publicação: 2012
• Outros Autores: Silva, José Antônio Aleixo da, Cordeiro, Gauss Moutinho, Ferreira, Rinaldo Luiz Caraciolo
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Ciência Florestal (Online)
• Texto Completo: https://periodicos.ufsm.br/cienciaflorestal/article/view/7558
• topic: maximum likelihood; symmetrical models; robust distributions; máxima verossimilhança; modelos simétricos; distribuições robustas

http://dx.doi.org/10.5902/198050987558The objective of this work was to estimate the height growth of Eucalyptus using the Chapman-Richards model considering for the errors the distributions normal, Student t (t) and Cauchy. The data set came from a hybrid of Eucalyptus urophylla x Eucalyptus tereticornis x E. pellita (controlled pollination), of the Forestry Experimental Module in the Gypsum Pole of Araripe, established in 2002. Eighty-three trees were used which heights were measured in all trees for six and half years. The fittings consisted on the estimation of the parameters of the Chapman-Richards model maximizing the log-likelihood of the error distributions using the symmetric distributions normal, t and Cauchy. For comparison of the adjusted models were used the criteria of Akaike Information Criterion (AIC) and Bayesian (BIC) and the mean absolute percentage error (MAPE). The model using the t distribution with 2 degrees of freedom (t2) had lower values of AIC and BIC and the model of Cauchy had lower value for MAPE. The results indicate that the model considering the t distribution for the errors presented best estimates of height growth of Eucalyptus clones in Gypsum Pole of Pernambuco.