Fitting a taper function to minimize the sum of absolute deviations

Scientia Agricola

Lana Mirian Santos Da Silva²  Luiz Carlos Estraviz Rodriguez¹  José Vicente Caixeta Filho¹  Simone Carolina Bauch¹ 

[1] ,Athena Recursos NaturaisPiracicaba SP ,Brasil

关键词: MOTAD;    ordinary least squares;    goal programming;    linear regression;    minimização do desvio absoluto total;    mínimos quadrados ordinários;    programação por metas;    regressão linear;   

DOI  :  10.1590/S0103-90162006000500007

来源: SciELO

【 摘 要 】

Multiple product inventories of forests require accurate estimates of the diameter, length and volume of each product. Taper functions have been used to precisely describe tree form, once they provide estimates for the diameter at any height or the height at any diameter. This study applied a goal programming technique to estimate the parameters of two taper functions to describe individual tree forms. The goal programming formulation generates parameters that minimize total absolute deviations (MOTAD). These parameters generated by the MOTAD method were compared to those of ordinary least squares (OLS) method. The analysis used a set of 178 trees cut from cloned eucalyptus plantations in the Southern part of the state of Bahia, Brazil. The values of the estimated parameters for the two taper functions resulted very similar when the two methods were compared. There was no significant difference between the two fitting methods according to the statistics used to evaluate the quality of the generated estimates. OLS and MOTAD resulted equally precise in the estimation of diameters and volumes outside and inside bark.

【 授权许可】

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