Criteria for the equality between ordinary least squares and best linear unbiased estimators under certain linear models

DOI10.2307/3315067zbMath0645.62072OpenAlexW2033721378MaRDI QIDQ3788917

Jerzy K. Baksalary

Publication date: 1988

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/3315067

zbMATH Keywords

linear modelsbest linear unbiased estimatorordinary least-squares estimatorone-way classificationheterogeneous variancestwo-way classification modelsnew necessary and sufficient conditiontwofold nested classification

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Analysis of variance and covariance (ANOVA) (62J10)

Related Items

Comparing the BLUEs Under Two Linear Models ⋮ On the equivalence of the BLUEs under a general linear model and its restricted and stochastically restricted models ⋮ Matrix rank and inertia formulas in the analysis of general linear models ⋮ An alternative form of the Watson efficiency ⋮ Applied regression analysis bibliography update 1988-89

Cites Work

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• On equalities between BLUES, WLSEs, and SLSEs
• Categorical information and the singular linear model