Identification and modeling of residual autocorrelation in the adjustments of wood's model to lactation curves of goats/Identificacao e modelagem da autocorrelacao residual no ajuste do modelo de wood as curvas de lactacao de cabras

The objective of this research was to present a methodology for identification and modeling of residual autocorrelation considering individual adjustments of the Wood's model to lactation dairy goats and evaluate the influence of such modeling in the quality of adjustment. The Wood's model...

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Veröffentlicht in:Ciência rural 2011-10, Vol.41 (10), p.1818
Hauptverfasser: de Melo, Ana Lucia Puerro, Torres, Robledo de Almeida, Ribeiro, Jose Ivo Jr, Fonseca e Silva, Fabyano, Rodrigues, Marcelo Teixeira, Gomes, Felipe da Silva, Brito, Luiz Fernando
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Zusammenfassung:The objective of this research was to present a methodology for identification and modeling of residual autocorrelation considering individual adjustments of the Wood's model to lactation dairy goats and evaluate the influence of such modeling in the quality of adjustment. The Wood's model was adjusted individually for lactations in three different ways, the first have assumed independence of errors (IE) for all lactations, the second have assumed autoregressives first order errors (AR1) for all lactations and the third, named (IE-AR1), was used the AR1 errors structure only for lactations that showed residual autocorrelation according to Durbin-Watson test, and the IE errors structure for the other lactations. The three ways of adjustment were compared by the percentage of convergence and the average of the mean square errors (MSE) and coefficients of determination adjusted ([R.sup.2]adj). The average of MSE and [R.sup.2]aj were very similar in the three cases of residual structure. However, the model with IE-AR1 residual structure showed a higher rate of convergence, which is an advantage, as it allows a greater number of animals are evaluated for their lactation curve. Therefore, due to the increasing convergence obtained, the fit of the Wood's model with IE-AR1 residual structure is the option most suitable for large data sets. Key words: autoregressives errors, Durbin-Watson, independent errors. Objetivou-se com este trabalho apresentar uma metodologia de identificacao e modelagem da autocorrelacao residual considerando ajustes individuais do modelo de Wood as lactacoes de cabras leiteiras e tambem avaliar a influencia de tal modelagem na qualidade do ajuste. O modelo de Wood foi ajustado individualmente as lactacoes, considerando tres estruturas residuais. Na primeira, assumiu-se independencia dos erros (EI) para todas as lactacoes, na segunda, assumiuse a estrutura de erros autoregressivos de primeira ordem (AR1) para todas as lactacoes e, na terceira, nomeada por EI-AR1, foi utilizada a estrutura de erros AR1 somente para as lactacoes que apresentaram autocorrelacao residual, segundo o teste de Durbin-Watson, e de EI para as demais. As tres situacoes de ajuste foram comparadas pelos percentuais de convergencia e pelas medias dos quadrados medios dos erros (QME) e dos coeficientes de determinacao ajustados ([R.sup.2]aj). As medias dos QME e dos [R.sup.2]aj apresentaram valores semelhantes nas tres situacoes de estrutura residual. No entanto, o model
ISSN:0103-8478