On the performance of the ordinary least squares method under an error component model.
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Publication:5953730
DOI10.1007/BF02742874zbMath1093.62556OpenAlexW3125548467MaRDI QIDQ5953730
Rainer Schwabe, Parimal Mukhopadhyay
Publication date: 29 January 2002
Published in: Metrika (Search for Journal in Brave)
Full work available at URL: https://eudml.org/doc/176768
Cites Work
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- A new bound for the Euclidean norm of the difference between the least squares and the best linear unbiased estimators
- On ordinary least-squares methods for sample surveys
- Optimum designs for multi-factor models
- Transformations for Estimation of Linear Models with Nested-Error Structure
- Finite Sample Efficiency of Ordinary Least Squares in the Linear Regression Model with Autocorrelated Errors
- The inefficiency of least squares
- On the minimum efficiency of least squares
- The Effect of Two-Stage Sampling on Ordinary Least Squares Methods
- On Canonical Forms, Non-Negative Covariance Matrices and Best and Simple Least Squares Linear Estimators in Linear Models
- Comparison of Least Squares and Minimum Variance Estimates of Regression Parameters
- Linear Statistical Inference and its Applications
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