Variance component estimation by resampling
1992
García-Cortés, L.A. | Moreno, C. | Varona, L. | Altarriba, J.
SUMMARY: A method to avoid the inverse of the coefficient matrix of the mixed model equation is presented. This method makes use of Monte Carlo samples that have been simulated with the same information matrix as the data and is applied to approximate the restricted maximum likelihood variance component estimation via EM algorithm. The results were analyzed in a single trait and single record animal model. The different size data samples used to analyze this procedure were simulated with selection. The computational cost of this algorithm is proportional to the number of random variables in the model. The variability of estimates was satisfactory, and more efficient when sample size increased.
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