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Some equivalences in linear estimation (in Russian)

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Author Info
Dmitry Danilov (Eindhoven University of Technology, Netherlands)
Jan R. Magnus (Tilburg University, Netherlands)

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Abstract

Under 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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Publisher Info
Article provided by Quantile in its journal Quantile.

Volume (Year): (2007)
Issue (Month): 3 (September)
Pages: 83-90
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:qnt:quantl:y:2007:i:3:p:83-90

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Web page: http://quantile.ru/

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Related research
Keywords: 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: General - - - Bayesian Analysis
C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis
C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques

Statistics
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This page was last updated on 2009-11-22.

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