On matrix-variate regression analysis

被引：29

作者：

Viroli, Cinzia ^{[1
]}

机构：

[1] Univ Bologna, Dept Stat, Bologna, Italy

来源：

JOURNAL OF MULTIVARIATE ANALYSIS | 2012年 / 111卷

关键词：

Linear regression; Maximum likelihood; Random matrix; Three-way data; GROWTH CURVE MODEL; LIKELIHOOD RATIO TEST; MULTIVARIATE; SEPARABILITY;

D O I：

10.1016/j.jmva.2012.04.005

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：

Three-way data arise in different application domains when multiple responses are measured at different time points or locations. A new regression model for analyzing three-way data is proposed. By assuming the matrix normal distribution for the error term, we will show that the proposed model represents the natural generalization of multiple and multivariate regression analysis. Inferential properties of the model estimators are derived. The model fit is illustrated on a real application. (C) 2012 Elsevier Inc. All rights reserved.

引用

页码：296 / 309

页数：14

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