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Some equivalences in linear estimation (in Russian)

Author

Listed:
  • Dmitry Danilov

    (Eindhoven University of Technology, Netherlands)

  • Jan R. Magnus

    (Tilburg University, Netherlands)

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.

Suggested Citation

  • Dmitry Danilov & Jan R. Magnus, 2007. "Some equivalences in linear estimation (in Russian)," Quantile, Quantile, issue 3, pages 83-90, September.
  • Handle: RePEc:qnt:quantl:y:2007:i:3:p:83-90
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    File URL: http://quantile.ru/03/03-DM.pdf
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    References listed on IDEAS

    as
    1. Franco Visani, 2017. "Applying business analytics for performance measurement and management. The case study of a software company," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2017(2), pages 89-123.
    2. repec:bla:revinw:v:46:y:2000:i:3:p:329-50 is not listed on IDEAS
    3. 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.
    4. John M. Abowd & Robert H. Creecy & Francis Kramarz, 2002. "Computing Person and Firm Effects Using Linked Longitudinal Employer-Employee Data," Longitudinal Employer-Household Dynamics Technical Papers 2002-06, Center for Economic Studies, U.S. Census Bureau.
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    Citations

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    Cited by:

    1. Van Tongeren, J.W. & Magnus, J.R., 2011. "Bayesian Integration of Large Scale SNA Data Frameworks with an Application to Guatemala," Other publications TiSEM 7a0ed98e-134b-4fa4-a97c-4, Tilburg University, School of Economics and Management.
    2. Van Tongeren, J.W. & Magnus, J.R., 2011. "Bayesian Integration of Large Scale SNA Data Frameworks with an Application to Guatemala," Discussion Paper 2011-022, Tilburg University, Center for Economic Research.
    3. 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.
    4. Van Tongeren, J.W., 2011. "From national accounting to the design, compilation, and use of bayesian policy and analysis frameworks," Other publications TiSEM e2d6399b-fdf5-4147-b414-3, Tilburg University, School of Economics and Management.
    5. Temel, Tugrul, 2011. "Estimation of a system of national accounts: implementation with mathematica," MPRA Paper 35446, University Library of Munich, Germany.

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    More about this item

    Keywords

    Linear Bayes estimation; best linear unbiased; least squares; sparse problems; large-scale optimization;
    All these keywords.

    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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