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Measures of correlation and computer algebra

Author

Listed:
  • Halkos, George
  • Tsilika, Kyriaki

Abstract

Our contribution in this work is to set the directions for specialized econometric computations in a free computer algebra system, Xcas. We focus on the programming of a routine dedicated to correlation criteria for multiple regression models. We program several operations for detecting and evaluating collinearity by applying the diagnostic techniques of linear regression analysis. Xcas could constitute a supplemental tool in a collinear data study. Its use is proposed complementary to established econometric software or as substitute software.

Suggested Citation

  • Halkos, George & Tsilika, Kyriaki, 2016. "Measures of correlation and computer algebra," MPRA Paper 70200, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:70200
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    References listed on IDEAS

    as
    1. George Halkos & Kyriaki Tsilika, 2015. "Programming Identification Criteria in Simultaneous Equation Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 157-170, June.
    2. A. Merckens & P. A. Bekker, 1993. "Identification of simultaneous equation models with measurement error: a computerized evaluation," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 47(4), pages 233-244, December.
    3. Belsley, David A, 1999. "Mathematica as an Environment for Doing Economics and Econometrics," Computational Economics, Springer;Society for Computational Economics, vol. 14(1-2), pages 69-87, October.
    4. Jinhu Li & Jeffrey S. Racine, 2008. "Maxima: An open source computer algebra system," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(4), pages 515-523.
    5. Grigory Bautin & Valery Kalyagin & Alexander Koldanov & Petr Koldanov & Panos Pardalos, 2013. "Simple measure of similarity for the market graph construction," Computational Management Science, Springer, vol. 10(2), pages 105-124, June.
    6. David A. Belsley, 1988. "A Guide to Using the Collinearity Diagnostics," Boston College Working Papers in Economics 190, Boston College Department of Economics.
    7. H. M. Amman & D. A. Kendrick & J. Rust (ed.), 1996. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 1, number 1.
    8. Friendly, Michael & Kwan, Ernest, 2009. "Where's Waldo? Visualizing Collinearity Diagnostics," The American Statistician, American Statistical Association, vol. 63(1), pages 56-65.
    9. Kendrick, David A & Amman, Hans M, 1999. "Programming Languages in Economics," Computational Economics, Springer;Society for Computational Economics, vol. 14(1-2), pages 151-181, October.
    10. Oleg Shirokikh & Grigory Pastukhov & Vladimir Boginski & Sergiy Butenko, 2013. "Computational study of the US stock market evolution: a rank correlation-based network model," Computational Management Science, Springer, vol. 10(2), pages 81-103, June.
    11. Kenneth A. Bollen & Shawn Bauldry, 2010. "Model Identification and Computer Algebra," Sociological Methods & Research, , vol. 39(2), pages 127-156, November.
    12. Hutton, John & Hutton, James, 1995. "The Maple Computer Algebra System: A Review," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(3), pages 329-337, July-Sept.
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    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

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