Fitting a taper function to minimize the sum of absolute deviations
Autor(a) principal: | |
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Data de Publicação: | 2006 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Scientia Agrícola (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162006000500007 |
Resumo: | 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. |
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Scientia Agrícola (Online) |
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Fitting a taper function to minimize the sum of absolute deviationsMOTADordinary least squaresgoal programminglinear regressionMultiple 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.Escola Superior de Agricultura "Luiz de Queiroz"2006-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162006000500007Scientia Agricola v.63 n.5 2006reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USP10.1590/S0103-90162006000500007info:eu-repo/semantics/openAccessSilva,Lana Mirian Santos daRodriguez,Luiz Carlos EstravizCaixeta Filho,José VicenteBauch,Simone Carolinaeng2006-09-20T00:00:00Zoai:scielo:S0103-90162006000500007Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2006-09-20T00:00Scientia Agrícola (Online) - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Fitting a taper function to minimize the sum of absolute deviations |
title |
Fitting a taper function to minimize the sum of absolute deviations |
spellingShingle |
Fitting a taper function to minimize the sum of absolute deviations Silva,Lana Mirian Santos da MOTAD ordinary least squares goal programming linear regression |
title_short |
Fitting a taper function to minimize the sum of absolute deviations |
title_full |
Fitting a taper function to minimize the sum of absolute deviations |
title_fullStr |
Fitting a taper function to minimize the sum of absolute deviations |
title_full_unstemmed |
Fitting a taper function to minimize the sum of absolute deviations |
title_sort |
Fitting a taper function to minimize the sum of absolute deviations |
author |
Silva,Lana Mirian Santos da |
author_facet |
Silva,Lana Mirian Santos da Rodriguez,Luiz Carlos Estraviz Caixeta Filho,José Vicente Bauch,Simone Carolina |
author_role |
author |
author2 |
Rodriguez,Luiz Carlos Estraviz Caixeta Filho,José Vicente Bauch,Simone Carolina |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Silva,Lana Mirian Santos da Rodriguez,Luiz Carlos Estraviz Caixeta Filho,José Vicente Bauch,Simone Carolina |
dc.subject.por.fl_str_mv |
MOTAD ordinary least squares goal programming linear regression |
topic |
MOTAD ordinary least squares goal programming linear regression |
description |
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. |
publishDate |
2006 |
dc.date.none.fl_str_mv |
2006-10-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162006000500007 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162006000500007 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0103-90162006000500007 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Escola Superior de Agricultura "Luiz de Queiroz" |
publisher.none.fl_str_mv |
Escola Superior de Agricultura "Luiz de Queiroz" |
dc.source.none.fl_str_mv |
Scientia Agricola v.63 n.5 2006 reponame:Scientia Agrícola (Online) instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Scientia Agrícola (Online) |
collection |
Scientia Agrícola (Online) |
repository.name.fl_str_mv |
Scientia Agrícola (Online) - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
scientia@usp.br||alleoni@usp.br |
_version_ |
1748936460176719872 |