A bound for the Euclidean norm of the difference between the least squares and the best linear unbiased estimators

DOI10.1214/aos/1176344383zbMath0392.62051OpenAlexW2011115910MaRDI QIDQ1251877

Jerzy K. Baksalary, Radosław Kala

Publication date: 1978

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1176344383

zbMATH Keywords

Best Linear Unbiased EstimatorsBoundEuclidean NormHabermanLeast Squares EstimatorsLinear ModelNonsingular Covariance Structure

Mathematics Subject Classification ID

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

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