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The Journey from Entropy to Generalized Maximum Entropy

Author

Listed:
  • D. Al-Nasser, Amjad

    (Professor, Department of Statistics, Science Faculty, Yarmouk University, Irbid 21163, Jordan.)

Abstract
Currently we are witnessing the revaluation of huge data recourses that should be analyzed carefully to draw the right decisions about the world problems. Such big data are statistically risky since we know that the data are combination of (useful) signals and (useless) noise, which considered as unorganized facts that need to be filtered and processed. Using the signals only and discarding the noise means that the data restructured and reorganized to be useful and it is called information. So for any data set, we need only the information. In context of information theory, the entropy is used as a statistical measure to quantify the maximum amount of information in a random event.

Suggested Citation

  • D. Al-Nasser, Amjad, 2019. "The Journey from Entropy to Generalized Maximum Entropy," Journal of Quantitative Methods, University of Management and Technology, Lahore, Pakistan, vol. 3(1), pages 1-7.
    • Handle: RePEc:ris:jqmumt:0018
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    File URL: https://ojs.umt.edu.pk/index.php/jqm/article/view/32/21
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    More about this item

    Keywords

    Entropy; Generalized Maximum Entropy; Maximum Entropy (ME); Mathematical Programming Problem;
    All these keywords.

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions

    Statistics

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