Characterizing Relationships Between Estimations Under a General Linear Model with Explicit and Implicit Restrictions by Rank of Matrix
DOI10.1080/03610926.2011.594537zbMath1271.62152OpenAlexW2149656302MaRDI QIDQ2920061
Publication date: 23 October 2012
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2011.594537
Moore-Penrose inverseBLUEOLSEmatrix rank methodequality of estimationsrestricted linear modelimplicitly restricted model
Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Parametric inference under constraints (62F30) Basic linear algebra (15A99)
Related Items (5)
Cites Work
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- A note on comparing the unrestricted and restricted least-squares estimators
- On the natural restrictions in the singular Gauss-Markov model
- Characterizations of admissible linear estimators in restricted linear models
- Representations of best linear unbiased estimators in the Gauss-Markoff model with a singular dispersion matrix
- Best affine unbiased representations of the fully restricted general Gauss--Markov model
- On equality and proportionality of ordinary least squares, weighted least squares and best linear unbiased estimators in the general linear model
- More on maximal and minimal ranks of Schur complements with applications
- The Treatment of Linear Restrictions in Regression Analysis
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