Page 350 - Linear Models for the Prediction of Animal Breeding Values 3rd Edition

Quaas, R.L. and Pollak, E.J. (1980) Mixed model methodology for farm and ranch
beef cattle testing programs. Journal of Animal Science 51, 1277–1287.
Quaas, R.L. and Pollak, E.J. (1981) Modified equations for sire models with groups.
Journal of Dairy Science 64, 1868–1872.
Robertson, A. and Rendel, J.M. (1954) The performance of heifers got by artificial
insemination. Journal of Agricultural Science, Cambridge 44, 184–192.
Ronningen, K. and Van Vleck, L.D. (1985) Selection index theory with practical
applications. In: Chapman, A.B. (ed.) General and Quantitative Genetics. World
Animal Science, A4, Elsevier Science Publishers, Oxford.
Schaeffer, L.R. (1984) Sire and cow evaluation under multiple trait models. Journal of
Dairy Science 67, 1567–1580.
Schaeffer, L.R. (1994) Multiple-country comparison of dairy sires. Journal of Dairy
Science 77, 2671–2678.
Schaeffer, L.R. (2004) Application of random regression models in animal breeding.
Livestock Production Science 86, 35–45.
Schaeffer, L.R. and Dekkers, J.C.M. (1994) Random regression in animal models for
test-day production in dairy cattle. In: Proceedings of the 5th World Congress
Applied to Livestock Production, Guelph, Canada, pp. 443–446.
Schaeffer, L.R. and Kennedy, B.W. (1986) Computing solutions to mixed model equa-
tions. In: Proceedings of the 3rd World Congress on Genetics Applied to Livestock
Production, Lincoln, NE, p. 392.
Schaeffer, L.R. and Wilton, J.W. (1987) RAM computing strategies and multiple
traits. Prediction of genetic value for beef cattle. In: Proceedings Workshop II,
Winrock, Kansas City, MO.
Schaeffer, L.R., Wilton, J.W. and Thompson, R. (1978) Simultaneous estimation of
variance and covariance components from multitrait mixed model equations.
Biometrics 34, 199–208.
Schaeffer, L.R., Jamrozik, J., Kistemaker, G.J. and van Doormaal, B.J. (2000)
Experience with a test day model. Journal of Dairy Science 83, 1135–1144.
Searle, S.R. (1982) Matrix Algebra Useful for Statistics. John Wiley & Sons, New York.
Sigurdsson, A. and Banos, G. (1995) Dependent variables in international sire evalu-
ations. Acta Agriculturæ Scandinavica 45, 209–217.
Solberg, T.R., Sonesson, A.K., Woolliams, J.A., Ødegard, J. and Meuwissen, T.H.E.
(2009) Persistence of accuracy of genomic-wide breeding values over generations
when including a polygenic effect. Genetics Selection Evolution 41, 53.
Sorensen, D. and Gianola, D. (2002) Likelihood, Bayesian, and MCMC Methods in
Quantitative Genetics. Springer-Verlag, New York.
Sorensen, D.A. and Kennedy, B.W. (1983) The use of the relationship matrix to
account for genetic drift variance in the analysis of genetic experiments. Theoretical
and Applied Genetics 66, 217–220.
Sorensen, D.A., Andersen, S. and Gianola, D. (1995) Bayesian inference in threshold
models using Gibbs sampling. Genetics Selection Evolution 27, 229–249.
Stranden, I. and Lidauer, M. (1999) Solving large mixed linear models using precon-
ditioned conjugate gradient iteration. Journal of Dairy Science 82, 2779–2787.
Szyda, J., Liu, Z., Reinhardt, F. and Reents, R. (2003) Incorporation of QTL informa-
tion into routine estimation of breeding values for German Holstein dairy cattle.
In: Proceedings of the 54th Annual Meeting of the European Association for
Animal Production, Rome, 2003, p. 11.

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