An extension of a rank criterion for the least squares estimator to be the best linear unbiased estimator

DOI10.1016/0378-3758(77)90015-5zbMath0383.62041OpenAlexW2022583062MaRDI QIDQ1248868

Jerzy K. Baksalary, Radosław Kala

Publication date: 1977

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(77)90015-5

Mathematics Subject Classification ID

Linear regression; mixed models (62J05)

Related Items (7)

On connections among OLSEs and BLUEs of whole and partial parameters under a general linear model ⋮ On the equality of estimators under a general partitioned linear model with parameter restrictions ⋮ Fundamental Equations of BLUE and BLUP in the Multivariate Linear Model with Applications ⋮ Characterizations of the best linear unbiased estimator in the general Gauss-Markov model with the use of matrix partial orderings ⋮ Simple least squares estimation versus best linear unbiased prediction ⋮ Matrix rank and inertia formulas in the analysis of general linear models ⋮ On equality of ordinary least squares estimator, best linear unbiased estimator and best linear unbiased predictor in the general linear model

Cites Work

• On Canonical Forms, Non-Negative Covariance Matrices and Best and Simple Least Squares Linear Estimators in Linear Models
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