We present evidence of 'generalized autoregressive conditional heteroskedasticity' (GARCH(1,1)), in the residuals of growth traits from beef cattle. This process can account for differences in variance at different times. Data used were from five herds registered in the national evaluation of Brangus in Argentina. The residuals were regressed on Julian dates by least squares. From a second set of residuals out of the linear regression model, Maximum Likelihood estimation via the Fisher scoring algorithm was used to estimate the GARCH(1,1) parameters. Eight out of fifteen one-sided Lagrange multiplier statistics significantly (P<0.05), rejected the hypothesis of null GARCH(1,1) parameters in the genetic evaluation residuals.
Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume , , 24.13, 2006
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