A generalization of Rao's covariance structure with applications to several linear models

DOI10.1006/jmva.1998.1771zbMath0941.62075OpenAlexW2059261660MaRDI QIDQ1275417

Hiroshi Kurata

Publication date: 13 August 2000

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1006/jmva.1998.1771

zbMATH Keywords

ordinary least squares estimatorGauss-Markov estimatorseemingly unrelated regression modelgeneral multivariate analysis of variance modelRao's covariance structure

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (3)

On equalities of estimations of parametric functions under a general linear model and its restricted models ⋮ Statistical analysis of a linear regression model with restrictions and superfluous variables ⋮ Covariance structure associated with an equality between two general ridge estimators

Cites Work

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• Linear Estimation with an Incorrect Dispersion Matrix in Linear Models with a Common Linear Part
• Note on a Condition for Equality of Sample Variances in a Linear Model
• The inefficiency of least squares
• On the minimum efficiency of least squares
• Some Finite Sample Results in the Context of Two Seemingly Unrelated Regression Equations
• Estimators for Seemingly Unrelated Regression Equations: Some Exact Finite Sample Results
• When are Gauss-Markov and Least Squares Estimators Identical? A Coordinate-Free Approach
• On Canonical Forms, Non-Negative Covariance Matrices and Best and Simple Least Squares Linear Estimators in Linear Models
• Tests for the independence between two seemingly unrelated regression equations

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