Burch B D, Harris I R
Department of Mathematics and Statistics, Northern Arizona University, Flagstaff 86011, USA.
Biometrics. 2001 Dec;57(4):1148-56. doi: 10.1111/j.0006-341x.2001.01148.x.
In this article, we estimate heritability or intraclass correlation in a mixed linear model having two sources of variation. In most applications, the commonly used restricted maximum likelihood (REML) estimator can only be obtained via an iterative approach. In some cases, the algorithm used to compute REML estimates may be slow or may even fail to converge. We develop a set of closed-form approximations to the REML estimator, and the performance of these estimators is compared with that of the REML estimator. We provide guidelines regarding how to choose the estimator that best approximates the REML estimator. Examples presented in the article suggest that the closed-form estimators compete with and, in some cases, outperform the REML estimator.
在本文中，我们在具有两个变异来源的混合线性模型中估计遗传力或组内相关。在大多数应用中，常用的限制最大似然（REML）估计器只能通过迭代方法获得。在某些情况下，用于计算REML估计的算法可能很慢，甚至可能无法收敛。我们开发了一组REML估计器的闭式近似，并将这些估计器的性能与REML估计器的性能进行了比较。我们提供了有关如何选择最接近REML估计器的估计器的指导方针。文章中给出的例子表明，闭式估计器与REML估计器竞争，并且在某些情况下优于REML估计器。
