On Admissibility of Linear Estimators with Respect to the Mean Square Error Matrix Criterion Under the General Mixed Linear Model

DOI10.1080/02331889908802681zbMath0947.62009OpenAlexW2225767153MaRDI QIDQ4943300

Augustyn Markiewicz, Jürgen Gross

Publication date: 31 October 2000

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331889908802681

zbMATH Keywords

linear estimationmean square error matrixgeneral mixed linear model

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Admissibility in statistical decision theory (62C15)

Related Items (3)

Admissibility of linear estimators for the stochastic regression coefficient in a general Gauss-Markoff model under a balanced loss function ⋮ Admissible Estimation for Linear Combination of Fixed and Random Effects in General Mixed Linear Models ⋮ Estimation and experiments comparison with respect to the matrix risk

Cites Work

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• Nonnegative and positive definiteness of matrices modified by two matrices of rank one
• A matrix inequality and admissibility of linear estimators with respect to the mean square error matrix criterion
• A study of the influence of the natural restrictions on estimation problems in the singular Gauss-Markov model
• Extension of the Gauss-Markov theorem to include the estimation of random effects
• Representations of best linear unbiased estimators in the Gauss-Markoff model with a singular dispersion matrix
• Categorical information and the singular linear model
• Necessary and sufficient conditions that linear estimators of a mixed effects linear model are admissible under matrix loss function

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