Estimation of main carcass components by using bootstrapping regression method
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Biometry and Genetics Unit, Department of Animal Science, Agriculture Faculty, University of Mustafa Kemal, 31034, Hatay, Turkey
Department of Animal Science, Agriculture Faculty, University of Çukurova, Adana, Turkey
Publication date: 2003-10-28
J. Anim. Feed Sci. 2003;12(4):723–737
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Bootstrap resampling methods have emerged as powerful tools for constructing inferential procedures in modern statistical data analysis. This article suggests an algorithm for building a regression model by bootstrap resampling method practically and gives parameter estimates of the model used for estimating main carcass components for Awassi lambs. Special attention is given to the estimation of regression parameters, their standard errors and confidence intervals using by bootstrapping regression method, and comparing results with ordinary least squares estimates. As result, so bootstrap regression method generally smaller standard errors and confidence intervals than ordinary least squares regression that the models MC (carcass muscle) = 214.198 + 3.808 MLL (muscle in long leg) + 4.866 MN (muscle in neck), BC (bone in carcass) = 605.904 + 3.641 BLL (bon in long leg) + 3.634 BN (bone in neck) and FC (fat in carcass) = -6283 + 716.8 CW (carcass weight) from bootstrapping regression method for estimation amount of muscle, bone and fat in carcass of fat tail Awassi lambs are more suitable than models from ordinary least squares method respectively.