Some equivalences in linear estimation (in Russian)
AbstractUnder normality, the Bayesian estimation problem, the best linear unbiased estimation problem, and the restricted least-squares problem are all equivalent. As a result we need not compute pseudo-inverses and other complicated functions, which will be impossible for large sparse systems. Instead, by reorganizing the inputs, we can rewrite the system as a new but equivalent system which can be solved by ordinary least-squares methods.
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Bibliographic InfoArticle provided by Quantile in its journal Quantile.
Volume (Year): (2007)
Issue (Month): 3 (September)
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Web page: http://quantile.ru/
Linear Bayes estimation; best linear unbiased; least squares; sparse problems; large-scale optimization;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
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- Temel, Tugrul, 2011. "Estimation of a system of national accounts: implementation with mathematica," MPRA Paper 35446, University Library of Munich, Germany.
- Danilov, Dmitry & Magnus, Jan R., 2008. "On the estimation of a large sparse Bayesian system: The Snaer program," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4203-4224, May.
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