Linear models that allow perfect estimation

DOI10.1007/s00362-012-0455-0zbMath1307.62178OpenAlexW2082184978MaRDI QIDQ2392705

Ronald Christensen, Yong Lin

Publication date: 2 August 2013

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-012-0455-0

zbMATH Keywords

general Gauss-Markov modellinear hypothesissingular covariance matrixbest linear unbiased estimate

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Point estimation (62F10)

Cites Work

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• Unbiased and minimum-variance unbiased estimation of estimable functions for fixed linear models with arbitrary covariance structure
• The general Gauss-Markov model with possibly singular dispersion matrix
• Some further remarks on the singular linear model
• Exact Linear Restrictions on Parameters in the General Linear Model with a Singular Covariance Matrix
• Goodness-of-Fit Tests for Parametric Regression Models
• On Canonical Forms, Non-Negative Covariance Matrices and Best and Simple Least Squares Linear Estimators in Linear Models
• On Best Linear Estimation and General Gauss-Markov Theorem in Linear Models with Arbitrary Nonnegative Covariance Structure

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