Inverse-partitioned-matrix method for the general Gauss-Markov model with linear restrictions

DOI10.1016/0378-3758(89)90084-0zbMath0695.62153OpenAlexW2049221267MaRDI QIDQ910133

Jerzy K. Baksalary, Pawel R. Pordzik

Publication date: 1989

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(89)90084-0

zbMATH Keywords

consistency conditionlinear restrictionsgeneral Gauss-Markov modelinverse-partitioned-matrix methodminimum dispersion linear unbiased estimators of estimable linear functionsminimum norm quadratic unbiased estimatorsingular model

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05)

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Cites Work

• Generalized inverses of partitioned matrices useful in statistical applications
• A note on the inverse-partitioned-matrix method in linear regression analysis
• On the independence of blocks of generalized inverses of bordered matrices
• Best linear unbiased estimation in the restricted general linear model²
• A note on best linear unbiased estimation in the restricted general linear model
• Categorical information and the singular linear model
• A Constrained Least Squares Approach to the General Gauss-Markov Linear Model
• On Best Linear Unbiased Estimation in the Restricted General Linear Model
• Corrigenda
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