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

机译:基于模糊表示的二项分布拟合优度检验的经验比较

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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:引入了实值随机变量的模糊表示,目的是通过相应的模糊值平均值捕获有关变量分布的相关信息。特别地,表征随机变量的模糊表示使我们能够捕获有关其分布的全部信息。这一事实的含义之一是,可以将有关模糊随机变量的模糊均值的检验用于开发拟合优度检验。在本文中,我们提出了基于虚假假设与某些特定的二项分布相关的拟合优度测试的经验比较,这些拟合优度测试基于一些方便的模糊表示法和众所周知的过程。

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