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The theory of dual co~event means

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  • Vorobyev, Oleg Yu.

Abstract

This work is the third, but not the last, in the cycle begun by the works [23, 22] about the new theory of experience and chance as the theory of co~events. Here I introduce the concepts of two co~event means, which serve as dual co~event characteristics of some co~event. The very idea of dual co~event means has become the development of two concepts mean-measure set [16] and mean-probable event [20, 24], which were first introduced as two independent characteristics of the set of events, so that then, within the framework of the theory of experience and of chance, the idea can finally get the opportunity to appear as two dual faces of the same co~event. I must admit that, precisely, this idea, hopelessly long and lonely stood at the sources of an indecently long string of guesses and insights, did not tire of looming, beckoning to the new co~event description of the dual nature of uncertainty, which I called the theory of experience and chance or the certainty theory. The constructive final push to the idea of dual co~event means has become two surprisingly suitable examples, with which I was fortunate to get acquainted in 2015, each of which is based on the statistics of the experienced-random experiment in the form of a co~event.

Suggested Citation

  • Vorobyev, Oleg Yu., 2016. "The theory of dual co~event means," MPRA Paper 81893, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:81893
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    References listed on IDEAS

    as
    1. Vorobyev, Oleg Yu., 2016. "Postulating the theory of experience and chance as a theory of co~events (co~beings)," MPRA Paper 81892, University Library of Munich, Germany.
    2. Brams, Steven J & Nagel, Jack H, 1991. "Approval Voting in Practice," Public Choice, Springer, vol. 71(1-2), pages 1-17, August.
    3. Vorobyev, Oleg Yu., 2016. "An element-set labelling a Cartesian product by measurable binary relations which leads to postulates of the theory of experience and chance as a theory of co~events," MPRA Paper 81891, University Library of Munich, Germany.
    4. Vorobyev, Oleg Yu., 2013. "In search of a primary source: remaking the paper (1975) where at the first time a definition of lattice (Vorob’ev) expectation of a random set was given," MPRA Paper 48102, University Library of Munich, Germany, revised 27 Apr 2013.
    5. Brams, Steven J. & Fishburn, Peter C., 1978. "Approval Voting," American Political Science Review, Cambridge University Press, vol. 72(3), pages 831-847, September.
    6. Vorobyev, Oleg Yu. & Lukyanova, Natalia A., 2013. "A Mean Probability Event for a Set of Events," MPRA Paper 48101, University Library of Munich, Germany.
    7. Fishburn, Peter C., 1978. "Axioms for approval voting: Direct proof," Journal of Economic Theory, Elsevier, vol. 19(1), pages 180-185, October.
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    Cited by:

    1. Vorobyev, Oleg Yu., 2016. "Triangle room paradox of negative probabilities of events," MPRA Paper 81894, University Library of Munich, Germany.
    2. Vorobyev, Oleg Yu., 2016. "An element-set labelling a Cartesian product by measurable binary relations which leads to postulates of the theory of experience and chance as a theory of co~events," MPRA Paper 81891, University Library of Munich, Germany.

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    More about this item

    Keywords

    Eventology; theory of experience and chance; event; co~event; experience; chance; to happen; to experience; to occur; probability; believability; mean-believable (mean-experienced) terraced braevent; mean-probable (mean-possible) ket-event; mean-believable-probability (mean-experienced-possible) co~event; experienced-random experiment; dual event means; dual co~event means; bra-menas; ket-means; Bayesian analysis; approval voting; forest approval voting.;
    All these keywords.

    JEL classification:

    • A1 - General Economics and Teaching - - General Economics
    • C0 - Mathematical and Quantitative Methods - - General
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • Z1 - Other Special Topics - - Cultural Economics
    • Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification

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