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The Soft Regression Method- Suggested Improvements

Author

Listed:
  • Eli Shnaider

    (Netanya Academic College 1 University St., Netanya, Israel)

  • Nava Haruvy

    (Netanya Academic College 1 University St., Netanya, Israel)

  • Arthur Yosef

    (Tel Aviv-Yaffo Academic College, 2 Rabenu Yeruham st., Tel Aviv-Yaffo, Israel)

Abstract

Soft regression is a regression technique based on fuzzy information processing and heuristic information processing methods. However, following the practical use of the method, it was found that two aspects of the calculations pertaining to the relative weights of explanatory variables could be improved to make the method more logical, and therefore more in line with heuristic basis of soft regression. In the following paper, we will present the soft regression method, the suggested improvements, and finally an example to illustrate the suggested improvements regarding factors affecting international growth and development.

Suggested Citation

  • Eli Shnaider & Nava Haruvy & Arthur Yosef, 2014. "The Soft Regression Method- Suggested Improvements," Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), vol. 0(2), pages 21-33, November.
    • Handle: RePEc:fzy:fuzeco:v:xix:y:2014:i:2:p:21-33
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    More about this item

    Keywords

    soft regression; similarity of numerical vectors; relative weight of explanatory variables; estimation of growth and development;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General

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