A test for variance-covarianch parameters in normal linear models

DOI10.1080/03610928508829050zbMath0586.62106OpenAlexW2120157495MaRDI QIDQ3711533

Robert K. Rayner

Publication date: 1985

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610928508829050

zbMATH Keywords

linear modelcommutative quadratic subspacechi-square variablesminimum norm quadratic unbiased estimationvariance-covariance parametersMINQUE estimatorsderived linear modelK-square testWald type test statistic

Mathematics Subject Classification ID

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

Cites Work

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• On the existence of unbiased nonnegative estimates of variance covariance components
• Nonnegative minimum biased invariant estimation in variance component models
• Estimating variance components in linear models
• Minimum variance quadratic unbiased estimation of variance components
• Linear models and convex geometry: aspects of non-negative variance estimation¹
• Three modifications of the principle of the minque
• Estimation of variance and covariance components—MINQUE theory
• Quadratic Subspaces and Completeness
• Linear Statistical Inference and its Applications
• Linear Spaces and Unbiased Estimation--Application to the Mixed Linear Model
• Application of the Method of Mixtures to Quadratic Forms in Normal Variates

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