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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
The results are applied to obtain the generalized inverse of X'V+X which ^ ields a solution of the normal equations snbject to nonestimable constraints on the parameters.
📌 3 Key Takeaways
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Objective & Hypothesis:in this paper we are concerned with the estimation of parameters snbject to linear constraints.
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Key Findings & Data:No rank conditions are imposed on R,X and V.
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Conclusion & Impact:The results are applied to obtain the generalized inverse of X'V+X which ^ ields a solution of the normal equations snbject to nonestimable constraints on the parameters.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Linear Restrictions · Parameters · linear regression
Abstract
in this paper we are concerned with the estimation of parameters snbject to linear constraints. No rank conditions are imposed on R,X and V. The results are applied to obtain the generalized inverse of X'V+X which ^ ields a solution of the normal equations snbject to nonestimable constraints on the parameters.
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Cite This Article
Akdeniz, F. (1980). Linear Restrictions on Parameters in linear regression model with non-spherical disturbalances. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, Volume: 29. https://doi.org/10.1501/Commua1_0000000074