Characterizations and dispersion-matrix robustness of efficiently estimable parametric functionals in linear models with nuisance parameters

DOI10.1016/0024-3795(90)90348-GzbMath0709.62063MaRDI QIDQ921781

Johan Fellman, Kenneth Nordström

Publication date: 1990

Published in: Linear Algebra and its Applications (Search for Journal in Brave)

zbMATH Keywords

characterizationsnuisance parameterslinear modelleast squares estimatorsbest linear unbiased estimatorsdispersion-matrix robustnessefficiently estimable parametric functionals

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear inference, regression (62J99)

Related Items (11)

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Cites Work

• Comparison of linear experiments with known covariances
• Löwner-ordering antitonicity of generalized inverses of Hermitian matrices
• Characterizations and dispersion-matrix robustness of efficiently estimable parametric functionals in linear models with nuisance parameters
• The matrix inequality \(M \leq B^*MB\)
• A rank characterization of linear models with nuisance parameters and its application to block designs
• General definition and decomposition of projectors and some applications to statistical problems
• Projections under seminorms and generalized Moore Penrose inverses
• Representations of best linear unbiased estimators in the Gauss-Markoff model with a singular dispersion matrix
• A study of the equivalence between a gauss-markoff model and its augmentation by nuisance parameters
• On Canonical Forms, Non-Negative Covariance Matrices and Best and Simple Least Squares Linear Estimators in Linear Models
• Range Decomposition and Generalized Inverse of Nonnegative Hermitian Matrices
• On the Efficiency of Experimental Designs
• Inequalities: theory of majorization and its applications
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