The objective of this study was to estimate genetic parameters using Bayesian inference for the estimates of individual parameters of mature weight (Â) and growth rate (<img border=0 width=32 height=32 id="_x0000_i1030" src="../../../../../../img/revistas/cr/2013nahead/a11813img06.gif">), obtained by Brody growth function. The file consisted of 14,563 records relating to weights and ages of 1,158 Nelore females, participants in the Genetic Improvement Program of the Nellore. For the estimates analysis of the curve parameters via Bayesian inference, it was used an univariated animal model that included as fixed effect of contemporary group (animals born on the same state, in the same quarter of the year, the same year and feedlot) and random as the direct genetic and residual. In this analysis it was used two different sizes for the chains generated by Gibbs sampling algorithm, 550 and 1.1 million cycles, with initial discarding of 50 000 and sample of 100 000 cycles, respectively, and sampled every 500 cycles and 1000, respectively. The mean posterior and residual additive genetic variance showed a small variation to both  and <img border=0 width=32 height=32 id="_x0000_i1031" src="../../../../../../img/revistas/cr/2013nahead/a11813img06.gif">, even when implemented in different sizes for the chains generated by Gibbs sampling algorithm. The heritability estimates for Â, ranged from 0.44 to 0.46, similar to the range 0.46 to 0.48 obtained for the estimates of <img border=0 width=32 height=32 id="_x0000_i1032" src="../../../../../../img/revistas/cr/2013nahead/a11813img06.gif">. These magnitudes indicate that the selection can be used as a tool to change the shape of the growth curve of these animals. However, the use of the information to amend the growth curve of animals, must be done with great care, since the traits to be worked in the modification of the shape of the growth curve according to the literature results are negatively correlated.
animal model; asymptotic weight; growth rate; Nellore breed
