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On Some Functional Characterizations of (Fuzzy) Set-Valued Random Elements

机译:关于(模糊)设定值随机元素的一些功能特征

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One of the most common spaces to model imprecise data through (fuzzy) sets is that of convex and compact (fuzzy) subsets in R~p. The properties of compactness and convexity allow the identification of such elements by means of the so-called support function, through an embedding into a functional space. This embedding satisfies certain valuable properties, however it is not always intuitive. Recently, an alternative functional representation has been considered for the analysis of imprecise data based on the star-shaped sets theory. The alternative representation admits an easier interpretation in terms of 'location' and 'imprecision', as a generalized idea of the concepts of mid-point and spread of an interval. A comparative study of both functional representations is made, with an emphasis on the structures required for a meaningful statistical analysis from the ontic perspective.
机译:模型不精确数据(模糊)集的最常见空间之一是R〜P中的凸和紧凑(模糊)子集的空间。紧凑性和凸起的性质允许通过嵌入功能空间来借助于所谓的支持功能识别这些元件。这种嵌入满足某些有价值的属性,但它并不总是直观。最近,已经考虑了基于星形集理论的不精确数据的替代功能表示。替代代表承认,在“地点”和“不精确”方面更容易解释,作为中点概念的概念和间隔的概念。对两种功能表示的比较研究进行了重点,重点是从联合角度来看有意义的统计分析所需的结构。

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