02001naa a2200265 a 450000100080000000500110000800800410001910000220006024501340008226000090021650001710022552010400039665000140143665000150145065000260146565300110149170000250150270000190152770000190154670000190156570000160158470000250160070000170162577300930164220990912019-02-25       2018    bl uuuu     u00u1 u    #d1 aSANTOS, P. M. dos  aUse of regularized quantile regression to predict the genetic merit of pigs for asymmetric carcass traits.h[electronic resource]  c2018  aTítulo em português: Uso da regressão quantílica regularizada para predição de mérito genético em suínos quanto a características assimétricas de carcaça.  aThe objective of this work was to evaluate the use of regularized quantile regression (RQR) to predict the genetic merit of pigs for asymmetric carcass traits, compared with the Bayesian lasso (Blasso) method. The genetic data of the traits carcass yield, bacon thickness, and backfat thickness from a F2 population composed of 345 individuals, generated by crossing animals from the Piau breed with those of a commercial breed, were used. RQR was evaluated considering different quantiles (? = 0.05 to 0.95). The RQR model used to estimate the genetic merit showed accuracies higher than or equal to those obtained by Blasso, for all studies traits. There was an increase of 6.7 and 20.0% in accuracy when the quantiles 0.15 and 0.45 were considered in the evaluation of carcass yield and bacon thickness, respectively. The obtained results are indicative that the regularized quantile regression presents higher accuracy than the Bayesian lasso method for the prediction of the genetic merit of pigs for asymmetric carcass variables.  aShrinkage  aSus scrofa  aSus Scrofa Domesticus  aBlasso1 aNASCIMENTO, A. C. C.1 aNASCIMENTO, M.1 aSILVA, F. F. e1 aAZEVEDO, C. F.1 aMOTA, R. R.1 aGUIMARÃES, S. E. F.1 aLOPES, P. S.  tPesquisa Agropecuária Brasileira, Brasília, DFgv. 53, n. 9, p. 1011-1017, Sept. 2018.