Comparison of Different Variance Component Estimation Approaches for MACE: Direct and Bottom-up PC

Author(s)
Tyriseva, A M
Meyer, Karin
Jakobsen, J
Ducrocq, V
Fikse, F
Lidauer, M H
Mantysaari, E A
Publication Date
2009
Abstract
Multiple-trait across country evaluation (MACE) is used for international genetic evaluation of dairy bulls. MACE treats records in different countries as different traits. Thus, a sire will get a breeding value for each participating country. Whenever a country makes changes to their national evaluation model, the genetic variance-covariance (VCV) matrix needs to be re-estimated. Estimation of the VCV matrix is a different task. For the Holstein production evaluation, which includes 26 traits, it is not possible to estimate the VCV matrix in a single analysis with the currently available estimation methods and the given time constraints. Hence, the complete matrix is built from analyses of sub-sets. This readily results in a non-positive matrix and a bending procedure (Jorjani et al., 2003) needs to be applied to obtain a positive definite matrix. In addition, the VCV matrix is usually over-parameterized as genetic correlations between countries are generally high.
Citation
Interbull Bulletin 40: Proceedings of the 2009 Interbull Meeting, v.40, p. 72-76
ISSN
1011-6079
Link
Language
en
Publisher
International Bull Evaluation Service
Title
Comparison of Different Variance Component Estimation Approaches for MACE: Direct and Bottom-up PC
Type of document
Conference Publication
Entity Type
Publication

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