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Estimation of non-linear growth models by linearization: a simulation study using a Gompertz function
Genetics Selection Evolution volume 38, Article number: 343 (2006)
Abstract
A method based on Taylor series expansion for estimation of location parameters and variance components of non-linear mixed effects models was considered. An attractive property of the method is the opportunity for an easily implemented algorithm. Estimation of non-linear mixed effects models can be done by common methods for linear mixed effects models, and thus existing programs can be used after small modifications. The applicability of this algorithm in animal breeding was studied with simulation using a Gompertz function growth model in pigs. Two growth data sets were analyzed: a full set containing observations from the entire growing period, and a truncated time trajectory set containing animals slaughtered prematurely, which is common in pig breeding. The results from the 50 simulation replicates with full data set indicate that the linearization approach was capable of estimating the original parameters satisfactorily. However, estimation of the parameters related to adult weight becomes unstable in the case of a truncated data set.
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Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Vuori, K., Strandén, I., Sevón-Aimonen, ML. et al. Estimation of non-linear growth models by linearization: a simulation study using a Gompertz function. Genet Sel Evol 38, 343 (2006). https://doi.org/10.1186/1297-9686-38-4-343
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DOI: https://doi.org/10.1186/1297-9686-38-4-343