Abstract
In this paper, iterative algorithms for computing restricted maximum likelihood (REML) estimates of variance components are discussed in the context of a possibly unbalanced, mixed linear model that contains a single set of m random effects. The coverage includes the Newton-Raphson algorithm, the method of scoring, the EM algorithm, and the method of successive approximations.
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© 1990 Springer-Verlag Berlin Heidelberg
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Harville, D.A., Callanan, T.P. (1990). Computational Aspects of Likelihood-Based Inference for Variance Components. In: Gianola, D., Hammond, K. (eds) Advances in Statistical Methods for Genetic Improvement of Livestock. Advanced Series in Agricultural Sciences, vol 18. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-74487-7_8
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DOI: https://doi.org/10.1007/978-3-642-74487-7_8
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