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Empirical Comparisons of Goodness-of-Fit Tests for Binomial Distributions Based on Fuzzy Representations

机译:基于模糊陈述的二项分子分布的高度拟合测试的经验比较

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Fuzzy representations of a real-valued random variable have been introduced with the aim of capturing relevant information on the distribution of the variable, through the corresponding fuzzy-valued mean value. In particular, characterizing fuzzy representations of a random variable allow us to capture the whole information on its distribution. One of the implications from this fact is that tests about fuzzy means of fuzzy random variables can be applied to develop goodness-of-fit tests. In this paper we present empirical comparisons of goodness-of-fit tests based on some convenient fuzzy representations with well-known procedures in case the null hypothesis relates to some specified Binomial distributions.
机译:通过相应的模糊值平均值捕获有关变量分布的相关信息,引入了实值随机变量的模糊表示。特别地,表征随机变量的模糊表示允许我们捕获其分布的整个信息。本事实的一个含义是,可以应用关于模糊随机变量的模糊装置的测试以开发拟合的拟合测试。在本文中,我们基于一些方便的模糊表示,在零假设涉及某些指定的二项份分布的情况下,基于一些方便的模糊表示,对良好的拟合模糊表示的实证比较。

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