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Restricted Maximum Likelihood to estimate variance components for mixed models with two random factors

Meyer, K.

Genetique Selection Evolution 19(1): 49-68

1987

A Restricted Maximum Likelihood procedure is described to estimate variance components for a univariate mixed model with two random factors. An EM-type algorithm is presented with a reparameterisation to speed up the rate of convergence. Computing strategies are outlined for models common to the analysis of animal breeding data, allowing for both a nested and a cross-classified design of the 2 random factors. Two special cases are considered: firstly, the total number of levels of fixed effects is small compared to th number of levels of both random factors ; secondly, one fixed effect with a large number of levels is to be fitted in addition to other fixed effects wtih few levels. A small numerical example is give to illustrate details.

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