Detalhes bibliográficos
Título da fonte: Repositório Institucional da UFMG
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oai_identifier_str oai:repositorio.ufmg.br:1843/31771
network_acronym_str UFMG
network_name_str Repositório Institucional da UFMG
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reponame_str Repositório Institucional da UFMG
instacron_str UFMG
institution Universidade Federal de Minas Gerais (UFMG)
instname_str Universidade Federal de Minas Gerais (UFMG)
spelling Ângela Maria Quintão Lanahttp://lattes.cnpq.br/2458995014564228Martinho de Almeida e SilvaFábio Luiz Buranelo ToralMiguel Houri Netohttp://lattes.cnpq.br/9124715219673779Natascha Almeida Marques da Silva2020-01-08T21:55:42Z2020-01-08T21:55:42Z2010-07-09http://hdl.handle.net/1843/31771O objetivo principal desse trabalho foi utilizar a análise de agrupamento para classificar e selecionar modelos não lineares de crescimento de bovinos Nelore tendo em vista os resultados de diferentes avaliadores de qualidade de ajuste. Ajustaram-se 12 modelos não-lineares, cuja qualidade de ajuste foi medida pelo coeficiente de determinação (R2), quadrado médio do erro (QME), critério de informação de Akaike (AIC), critério de informação Bayesiano (BIC), erro quadrático médio de predição (MEP) e coeficiente de determinação de predição (R2p). O modelo Brody foi o que apresentou o melhor ajuste para o conjunto de dados.This study aimed to evaluate cluster analysis in classifing and selecting non linear models to describe Nellore beef cattle growth based on different goodness of fit criteria tests. A total of 12 non linear models were evaluated based on the following criteria::determination coefficient (R2), error mean square (QME), Akaike information criterion (AIC), Bayesian information criterion (BIC), mean quadratic error of prediction (MEP) and predicted determination coefficient (R2p). The Brody model showed the best goodness of fit for this data set.CNPq - Conselho Nacional de Desenvolvimento Científico e TecnológicoporUniversidade Federal de Minas GeraisPrograma de Pós-Graduação em ZootecniaUFMGBrasilAnálise multivariadaModelos não linearesBovinos NeloreSeleções de modelos de regressão não lineares e aplicação do algoritmo saem na avaliação genética do crescimento de bovinos Neloreinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGORIGINALNATASCHA ALMEIDA MARQUES DA SILVA.pdfNATASCHA ALMEIDA MARQUES DA SILVA.pdfapplication/pdf1286292https://repositorio.ufmg.br/bitstream/1843/31771/1/NATASCHA%20ALMEIDA%20MARQUES%20DA%20SILVA.pdf04c1482117960629791acc6d90f455bbMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-82119https://repositorio.ufmg.br/bitstream/1843/31771/2/license.txt34badce4be7e31e3adb4575ae96af679MD52TEXTNATASCHA ALMEIDA MARQUES DA SILVA.pdf.txtNATASCHA ALMEIDA MARQUES DA SILVA.pdf.txtExtracted texttext/plain163378https://repositorio.ufmg.br/bitstream/1843/31771/3/NATASCHA%20ALMEIDA%20MARQUES%20DA%20SILVA.pdf.txtbf5f0a3a0c66bffad0455a359b495f44MD531843/317712020-01-09 03:29:53.115oai:repositorio.ufmg.br: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Repositório InstitucionalPUBhttps://repositorio.ufmg.br/oaiopendoar:2020-01-09T06:29:53Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
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