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 MX*(U,gθ), 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 F̃X-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. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Apolloni, B., Pedrycz, W., Bassis, S., & Malchiodi, D. (2008). Modeling samples. Studies in Computational Intelligence, 138, 45–64. https://doi.org/10.1007/978-3-540-79864-4_2
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