The objective of this study was to evaluate the residual autocorrelation effect on the estimates of genetic parameters for total milk yield (MY) and the coefficients a, b and c of Wood's model and, consequently, the animal's classification for these traits. Wood's model was fitted to the lactation of goats considering three cases of residual structure: (IE) - independent errors, (AR1) - first order autoregressive errors, and (IE - AR1) - AR1 errors only for lactations that had significant residual autocorrelation and IE for others. Estimates of the coefficients a, b and c and PL were used as dependent variables in a multivariate animal model, which included the random effects of animal and permanent environmental and fixed effects of contemporary group, number of foals per birth, genetic groups and order of calving, besides the covariates of lactation length (linear) and age at parturition (linear and quadratic). The different residual structures affected the estimates of genetic parameters and the classification of animals for the traits studied. Therefore, the selection of animals can be modified with the presence of residual autocorrelation and the structure IE-AR1 is presented as an alternative to solve this problem.
animal model; autoregressive errors; heritability; repeatability
