Recursive improvement of estimates in a Gauss-Markov model with linear restrictions

DOI10.2307/3314736zbMath0667.62050OpenAlexW2065615062MaRDI QIDQ3819847

K. Klaczynski, Radosław Kala

Publication date: 1988

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/3314736

zbMATH Keywords

recursive formulageneral Gauss-Markov modelestimable functionsdouble linear restrictionsminimum-dispersion linear unbiased estimator

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05)

Related Items (5)

Iterative Estimators of Parameters in Linear Models with Partially Variant Coefficients ⋮ Inclusion and exclusion of data or parameters in the general linear model ⋮ Comparing generalized mixed estimators with respect to covariance matrix in a linear regression model ⋮ Adjusting of estimates in general linear model with respect to linear restrictions ⋮ Applied regression analysis bibliography update 1988-89

Cites Work

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• Extensions of Milliken's estimability criterion
• Best linear unbiased estimation in the restricted general linear model²

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