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Part of the book series: Studies in Computational Intelligence ((SCI,volume 138))

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Abstract

We will assume the mechanism shown in Fig. 2.1 as the mother of all samples. You may see the contrivance in its center as a spring generating standard random numbers for free which are transmuted into numbers following a given distribution law after having passed through the gears of the mechanism. By default, we assume that the standard numbers are uniform in [0,1] like in this figure. Thus, we have an universal sampling mechanism \(\mathcal M^*_X(U,g_\theta)\), and you are ensured that, like from a cornucopia, you may draw any kind of random variable X, provided you may device the gears in order to compute the related \(\widetilde F_X^{-1}\) defined in Fact 1.4. Two considerations are in order to remove the wrong idea that we are univocally, hence a priori, describing the world.

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Âİ 2008 Springer-Verlag Berlin Heidelberg

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Apolloni, B., Pedrycz, W., Bassis, S., Malchiodi, D. (2008). Modeling Samples. In: The Puzzle of Granular Computing. Studies in Computational Intelligence, vol 138. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79864-4_2

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  • DOI: https://doi.org/10.1007/978-3-540-79864-4_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-79863-7

  • Online ISBN: 978-3-540-79864-4

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