Abbas Parchami, Przemyslaw Grzegorzewski, Maciej Romaniuk
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引用次数: 0
Abstract
Computer simulations are a powerful tool in many fields of research. This also applies to the broadly understood analysis of experimental data, which are frequently burdened with multiple imperfections. Often the underlying imprecision or vagueness can be suitably described in terms of fuzzy numbers which enable also the capture of subjectivity. On the other hand, due to the random nature of the experimental data, the tools for their description must take into account their statistical nature. In this way, we come to random fuzzy numbers that model fuzzy data and are also solidly formalized within the probabilistic setting. In this contribution, we introduce the so-called LR random fuzzy numbers that can be used in various Monte-Carlo simulations on fuzzy data. The proposed method of generating fuzzy numbers with membership functions given by probability densities is both simple and rich, well-grounded mathematically, and has a high application potential.
计算机模拟是许多研究领域的有力工具。这同样适用于对实验数据的广义分析，因为实验数据往往存在多种不完善之处。通常情况下，可以用模糊数来适当地描述潜在的不精确性或模糊性，模糊数还可以捕捉主观性。另一方面，由于实验数据的随机性，对其进行描述的工具必须考虑其统计性质。这样，我们就得出了能模拟模糊数据的随机模糊数，并在概率论环境中将其形式化。在本文中，我们介绍了所谓的 LR 随机模糊数，它可用于对模糊数据进行各种蒙特卡洛模拟。所提出的生成模糊数的方法，其成员函数由概率密度给出，既简单又丰富，具有坚实的数学基础，应用潜力很大。
期刊介绍：
The journal Statistical Papers addresses itself to all persons and organizations that have to deal with statistical methods in their own field of work. It attempts to provide a forum for the presentation and critical assessment of statistical methods, in particular for the discussion of their methodological foundations as well as their potential applications. Methods that have broad applications will be preferred. However, special attention is given to those statistical methods which are relevant to the economic and social sciences. In addition to original research papers, readers will find survey articles, short notes, reports on statistical software, problem section, and book reviews.
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