Identifiability of the random effects' covariance matrix of the linear mixed model

被引：0

作者：

Amestoy, Matteo ^{[1
]}

van de Wiel, Mark A. ^{[1
]}

van Wieringen, Wessel N. ^{[1
,2
]}

机构：

[1] Amsterdam UMC, Dept Epidemiol & Data Sci, Amsterdam, Netherlands

[2] Vrije Univ Amsterdam, Dept Math, Amsterdam, Netherlands

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2024年 / 53卷 / 21期

关键词：

Injectivity; normality; non linear parametrization;

D O I：

10.1080/03610926.2023.2272003

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Novel necessary and sufficient conditions for the identifiability of the linear mixed model are derived. These conditions either relax or generalize previously reported conditions. The novel conditions are translated to criteria that can be checked for most commonly employed parametrizations of the random effect's covariance matrix of linear mixed model.

引用

页码：7711 / 7722

页数：12

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