Maximum Likelihood Estimation of a Set of Covariance Matrices Under Lowner Order Restrictions with Applications to Balanced Multivariate Variance Components Models
Maximum Likelihood Estimation of a Set of Covariance Matrices Under Lowner Order Restrictions with Applications to Balanced Multivariate Variance Components Models
复制标题
低阶限制下一组协方差矩阵的最大似然估计及其在平衡多元方差分量模型中的应用
DOI：
10.1214/aos/1176348124
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发表时间：
1991
影响因子：
4.5
通讯作者：
R. Dykstra
中科院分区：
文献类型：
--
作者：
J. A. Calvin;R. Dykstra
本文研究了Lower序协方差阵的极大似然估计问题。它表明，这个问题的双重制定是听话的，在其本身的权利是重要的。原始问题和对偶问题之间的相互作用提出了计算这些问题的解的通用算法。该算法适用于平衡多元方差分量模型中的一些估计问题。本文还讨论了方差分量模型的收敛速度。
The problem of maximum likelihood estimation of Lowner ordered covariance matrices is considered. It is shown that a dual formulation of this problem is tractable and important in its own right. The interplay between the primal and dual problems suggests a general algorithm for computing the solutions to these problems. This algorithm has application to some estimation problems in balanced multivariate variance components models. The speed of convergence is also discussed for the variance components models.