Investigating growth models with linearization domain analysis and residual analysis

LOGIC JOURNAL OF THE IGPL(2023)

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摘要
Growth modelling is of interest to scientists in various disciplines. In our article, we will collect 17 models designed for growth modelling, appraise these models and contribute to the discussion of their applicability. The merit of the paper lies in studying the convergence properties of nonlinear regression in selected models. Our studies will be performed mainly concerning the quality of the obtained estimates, which are closely related to the intrinsic curvature of the model according to Bates and Watts. This curvature determines the size of the linearization domains. Only if the initial solution is in this domain, then the convergence of the estimate in nonlinear regression is guaranteed. The primary goal is to design a methodology for selecting a growth model. We will demonstrate fruitfulness of our methodology on the weight measurements of 10 calves under 25 months of age from cowsheds in the village Zaluzi in the Czech Republic. Estimated parameters of growth curves, sizes of linearization domain, calculated residues and coefficients of determination indices will be the subject of discussion.
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关键词
Growth models, animal growth, nonlinear regression, Bates and Watts curvature, linearization domain
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