Modelos não lineares generalizados aplicados na predição da área basal e volume de Eucalyptus clonal

• Autor(a) principal: Carvalho, Samuel de Pádua Chaves e
• Data de Publicação: 2011
• Outros Autores: Calegario, Natalino, Silva, Fabyano Fonseca e, Borges, Luís Antônio Coimbra, Mendonça, Adriano Ribeiro de, Lima, Mariana Peres de
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Institucional da UFLA
• Texto Completo: http://repositorio.ufla.br/jspui/handle/1/38974
• topic: Modelos estocásticos; Predição; Eucalipto - Crescimento; Produção florestal; Probability models; Prediction; Eucalyptus - Growth; Forestry yield

This paper aims to propose the use of generalized nonlinear models for prediction of basal area growth and yield of total volume of the hybrid Eucalyptus urocamaldulensis, in a stand situation in a central region in state of Minas Gerais. The used methodology allows to work with data in its original form without the necessity of transformation of variables, and generate highly accurate models. To evaluate the fitting quality, it was proposed the Bayesian information criterion, of the Akaike, and test the maximum likelihood, beyond the standard error of estimate, and residual graphics. The models were used with a good performance, highly accurate and parsimonious estimates of the variables proposed, with errors reduced to 12% for basal area and 4% for prediction of the volume.