Comparing non-linear mathematical models to describe growth of different animals Avaliação comparativa de modelos matemáticos não lineares para descrever o crescimento animal

Detalhes bibliográficos
Autor(a) principal: Teleken J.T.
Data de Publicação: 2017
Outros Autores: Galvao, Alessandro Cazonatto, Robazza, Weber Da Silva
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da Udesc
Texto Completo: https://repositorio.udesc.br/handle/UDESC/7321
Resumo: © 2017, Eduem - Editora da Universidade Estadual de Maringa. All rights reserved.The main objective of this study was to compare the goodness of fit of five non-linear growth models, i.e. Brody, Gompertz, Logistic, Richards and von Bertalanffy in different animals. It also aimed to evaluate the influence of the shape parameter on the growth curve. To accomplish this task, published growth data of 14 different groups of animals were used and four goodness of fit statistics were adopted: coefficient of determination (R2), root mean square error (RMSE), Akaike information criterion (AIC) and Bayesian information criterion (BIC). In general, the Richards growth equation provided better fits to experimental data than the other models. However, for some animals, different models exhibited better performance. It was obtained a possible interpretation for the shape parameter, in such a way that can provide useful insights to predict animal growth behavior.
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spelling Comparing non-linear mathematical models to describe growth of different animals Avaliação comparativa de modelos matemáticos não lineares para descrever o crescimento animal© 2017, Eduem - Editora da Universidade Estadual de Maringa. All rights reserved.The main objective of this study was to compare the goodness of fit of five non-linear growth models, i.e. Brody, Gompertz, Logistic, Richards and von Bertalanffy in different animals. It also aimed to evaluate the influence of the shape parameter on the growth curve. To accomplish this task, published growth data of 14 different groups of animals were used and four goodness of fit statistics were adopted: coefficient of determination (R2), root mean square error (RMSE), Akaike information criterion (AIC) and Bayesian information criterion (BIC). In general, the Richards growth equation provided better fits to experimental data than the other models. However, for some animals, different models exhibited better performance. It was obtained a possible interpretation for the shape parameter, in such a way that can provide useful insights to predict animal growth behavior.2024-12-06T13:24:41Z2017info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlep. 73 - 811807-867210.4025/actascianimsci.v39i1.31366https://repositorio.udesc.br/handle/UDESC/7321Acta Scientiarum - Animal Sciences391Teleken J.T.Galvao, Alessandro CazonattoRobazza, Weber Da Silvaengreponame:Repositório Institucional da Udescinstname:Universidade do Estado de Santa Catarina (UDESC)instacron:UDESCinfo:eu-repo/semantics/openAccess2024-12-07T20:53:50Zoai:repositorio.udesc.br:UDESC/7321Biblioteca Digital de Teses e Dissertaçõeshttps://pergamumweb.udesc.br/biblioteca/index.phpPRIhttps://repositorio-api.udesc.br/server/oai/requestri@udesc.bropendoar:63912024-12-07T20:53:50Repositório Institucional da Udesc - Universidade do Estado de Santa Catarina (UDESC)false
dc.title.none.fl_str_mv Comparing non-linear mathematical models to describe growth of different animals Avaliação comparativa de modelos matemáticos não lineares para descrever o crescimento animal
title Comparing non-linear mathematical models to describe growth of different animals Avaliação comparativa de modelos matemáticos não lineares para descrever o crescimento animal
spellingShingle Comparing non-linear mathematical models to describe growth of different animals Avaliação comparativa de modelos matemáticos não lineares para descrever o crescimento animal
Teleken J.T.
title_short Comparing non-linear mathematical models to describe growth of different animals Avaliação comparativa de modelos matemáticos não lineares para descrever o crescimento animal
title_full Comparing non-linear mathematical models to describe growth of different animals Avaliação comparativa de modelos matemáticos não lineares para descrever o crescimento animal
title_fullStr Comparing non-linear mathematical models to describe growth of different animals Avaliação comparativa de modelos matemáticos não lineares para descrever o crescimento animal
title_full_unstemmed Comparing non-linear mathematical models to describe growth of different animals Avaliação comparativa de modelos matemáticos não lineares para descrever o crescimento animal
title_sort Comparing non-linear mathematical models to describe growth of different animals Avaliação comparativa de modelos matemáticos não lineares para descrever o crescimento animal
author Teleken J.T.
author_facet Teleken J.T.
Galvao, Alessandro Cazonatto
Robazza, Weber Da Silva
author_role author
author2 Galvao, Alessandro Cazonatto
Robazza, Weber Da Silva
author2_role author
author
dc.contributor.author.fl_str_mv Teleken J.T.
Galvao, Alessandro Cazonatto
Robazza, Weber Da Silva
description © 2017, Eduem - Editora da Universidade Estadual de Maringa. All rights reserved.The main objective of this study was to compare the goodness of fit of five non-linear growth models, i.e. Brody, Gompertz, Logistic, Richards and von Bertalanffy in different animals. It also aimed to evaluate the influence of the shape parameter on the growth curve. To accomplish this task, published growth data of 14 different groups of animals were used and four goodness of fit statistics were adopted: coefficient of determination (R2), root mean square error (RMSE), Akaike information criterion (AIC) and Bayesian information criterion (BIC). In general, the Richards growth equation provided better fits to experimental data than the other models. However, for some animals, different models exhibited better performance. It was obtained a possible interpretation for the shape parameter, in such a way that can provide useful insights to predict animal growth behavior.
publishDate 2017
dc.date.none.fl_str_mv 2017
2024-12-06T13:24:41Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv 1807-8672
10.4025/actascianimsci.v39i1.31366
https://repositorio.udesc.br/handle/UDESC/7321
identifier_str_mv 1807-8672
10.4025/actascianimsci.v39i1.31366
url https://repositorio.udesc.br/handle/UDESC/7321
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Acta Scientiarum - Animal Sciences
39
1
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv p. 73 - 81
dc.source.none.fl_str_mv reponame:Repositório Institucional da Udesc
instname:Universidade do Estado de Santa Catarina (UDESC)
instacron:UDESC
instname_str Universidade do Estado de Santa Catarina (UDESC)
instacron_str UDESC
institution UDESC
reponame_str Repositório Institucional da Udesc
collection Repositório Institucional da Udesc
repository.name.fl_str_mv Repositório Institucional da Udesc - Universidade do Estado de Santa Catarina (UDESC)
repository.mail.fl_str_mv ri@udesc.br
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