2016
DOI: 10.1590/0103-8478cr20150473
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Abstract: The objective of this study was to compare the functions of Wilmink and Ali and Schaeffer with Legendre polynomials in random regression models using heterogeneous residual variances for modeling genetic parameters during the

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Cited by 4 publications
(4 citation statements)
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“…In studies by Brotherstone, White, and Meyer (2000), Pereira et al (2010) and Bignardi et al (2011) negative estimates of genetic correlations between yields made at the beginning and end of lactation were also reported. Difficulties of adjustment of genetic and permanent environmental correlations for LEG5 also were verified of Dornelles et al (2016). Note.…”
Section: Resultsmentioning
confidence: 87%
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“…In studies by Brotherstone, White, and Meyer (2000), Pereira et al (2010) and Bignardi et al (2011) negative estimates of genetic correlations between yields made at the beginning and end of lactation were also reported. Difficulties of adjustment of genetic and permanent environmental correlations for LEG5 also were verified of Dornelles et al (2016). Note.…”
Section: Resultsmentioning
confidence: 87%
“…This may be associated with the number of model parameters (LEG5) that needed to be adjusted (Table 5) and the lower number of test day in the last milk recording observations (Table 3). In a study by Costa et al (2008) and Dornelles et al (2016), problems with the fit of random regressions to extremes of lactation data were also observed and related to the highest number of parameters of this function. jas.ccsenet.…”
Section: Resultsmentioning
confidence: 99%
“…B-spline quadratic and cubic models of 8 th order for milk yield trait. While, Legendre polynomial functions were successfully converged for iterative process of 3 rd and 4 th orders (Padilha et al 2017), of 3 rd to 6 d th orders for MY, FY and PY (Biassus et al 2010), of 4 th order for MY (Naserkheil et al 2016) and of 3 rd to 5 d th orders for MY (Dornelles et al 2016). Comparison of efficiencies and selection of best fitted test day models of different orders: The goodness of fit of all TDM models was investigated using various criteria, viz.…”
Section: Datamentioning
confidence: 99%
“…Mostly higher orders of LP are suggested as best for various yield traits based on Log L and AIC e.g. 4 g Summary of effect-wise levels, mean, standard deviation, minimum and maximum values for TDMYPadilha et al (2017), 6 th order for MY, FY and PY byBiassus et al (2010), 6 th order of LP byBignardi et al (2011), 4 th order for MY byNaserkheil et al (2016) and 5 th order of LP for MY byDornelles et al (2016), 5 th and 6 th order of LP for AG effect and PE effect by…”
mentioning
confidence: 99%