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United States Department of Agriculture-Agricultural Research Service / University of Nebraska-Lincoln: Faculty Publications
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Full-Text Articles in Meat Science
Use Of Robust Multivariate Linear Mixed Models For Estimation Of Genetic Parameters For Carcass Traits In Beef Cattle, S. O. Peters, K. Kizilkaya, D. J. Garrick, R. L. Fernando, E. J. Pollak, R. Mark Enns, M. De Donato, O. O. Ajayi, I. G. Imumorin
Use Of Robust Multivariate Linear Mixed Models For Estimation Of Genetic Parameters For Carcass Traits In Beef Cattle, S. O. Peters, K. Kizilkaya, D. J. Garrick, R. L. Fernando, E. J. Pollak, R. Mark Enns, M. De Donato, O. O. Ajayi, I. G. Imumorin
United States Department of Agriculture-Agricultural Research Service / University of Nebraska-Lincoln: Faculty Publications
Assumptions of normality of residuals for carcass evaluation may make inferences vulnerable to the presence of outliers, but heavy-tail densities are viable alternatives to normal distributions and provide robustness against unusual or outlying observations when used to model the densities of residual effects. We compare estimates of genetic parameters by fitting multivariate Normal (MN) or heavy-tail distributions (multivariate Student’s t and multivariate Slash, MSt and MS) for residuals in data of hot carcass weight (HCW), longissimus muscle area (REA) and 12th to 13th rib fat (FAT) traits in beef cattle using 2475 records from 2007 to 2008 from a large …