On the robustness of least squares procedures in regression models

DOI10.1016/0047-259X(80)90053-6zbMath0444.62077MaRDI QIDQ1144877

Malay Ghosh, Bimal Kumar Sinha

Publication date: 1980

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

zbMATH Keywords

maximum likelihood estimateslinear hypotheseslikelihood ratio testsbalanced block designsmultivariate regression modelsintraclass correlation matrixleast squares proceduresnonnormal distributions of error

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Hypothesis testing in multivariate analysis (62H15) Robustness and adaptive procedures (parametric inference) (62F35) Statistical block designs (62K10)

Related Items (5)

Independence distribution preserving joint covariance structures for the multivariate two-group case ⋮ On the robustness of least squares procedures in regression models ⋮ Distribution of multivariate quadratic forms under certain covariance structures ⋮ Independence distribution preserving covariance structures for the multivariate linear model ⋮ Elliptical structural models

Cites Work

• On the robustness of least squares procedures in regression models
• On the Nonrandomized Optimality and Randomized Nonoptimality of Symmetrical Designs
• Bayesian and Non-Bayesian Analysis of the Regression Model with Multivariate Student-t Error Terms
• On Canonical Forms, Non-Negative Covariance Matrices and Best and Simple Least Squares Linear Estimators in Linear Models
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