Joining Iso-Structured Models with Commutative Orthogonal Block Structure

Q3 Mathematics
C. Santos, C. Dias, C. Nunes, J. Mexia
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引用次数: 0

Abstract

In this work, we focus on a special class of mixed models, named models with commutative orthogonal block structure (COBS), whose covariance matrix is a linear combination of known pairwise orthogonal projection matrices that add to the identity matrix, and for which the orthogonal projection matrix on the space spanned by the mean vector commutes with the covariance matrix. The COBS have least squares estimators giving the best linear unbiased estimators for estimable vectors. Our approach to COBS relies on their algebraic structure, based on commutative Jordan algebras of symmetric matrices, which proves to be advantageous as it leads to important results in the estimation. Specifically, we are interested in iso-structured COBS, applying to them the operation of models joining. We show that joining iso-structured COBS gives COBS and that the estimators for the joint model may be obtained from those for the individual models.
用交换正交块结构连接等结构模型
本文研究了一类特殊的混合模型,即交换正交块结构(COBS)模型,其协方差矩阵是已知的对正交投影矩阵与单位矩阵的线性组合,并且平均向量张成的空间上的正交投影矩阵与协方差矩阵交换。COBS具有最小二乘估计,给出了可估计向量的最佳线性无偏估计。我们的方法依赖于它们的代数结构,基于对称矩阵的交换Jordan代数,这被证明是有利的,因为它在估计中导致重要的结果。具体来说,我们对同结构COBS感兴趣,并将模型连接的操作应用于它们。我们证明了连接等结构COBS给出了COBS,并且联合模型的估计量可以从单个模型的估计量中得到。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
WSEAS Transactions on Mathematics
WSEAS Transactions on Mathematics Mathematics-Discrete Mathematics and Combinatorics
CiteScore
1.30
自引率
0.00%
发文量
93
期刊介绍: WSEAS Transactions on Mathematics publishes original research papers relating to applied and theoretical mathematics. We aim to bring important work to a wide international audience and therefore only publish papers of exceptional scientific value that advance our understanding of these particular areas. The research presented must transcend the limits of case studies, while both experimental and theoretical studies are accepted. It is a multi-disciplinary journal and therefore its content mirrors the diverse interests and approaches of scholars involved with linear algebra, numerical analysis, differential equations, statistics and related areas. We also welcome scholarly contributions from officials with government agencies, international agencies, and non-governmental organizations.
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