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Multiple and Partial Correlation Coefficients of Fuzzy Sets

机译:模糊集的多重和部分相关系数

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摘要

In many applications, multiple correlation and partial correlation for three or more fuzzy sets are very important, but Chiang and Lin (1999, Fuzzy Sets and Systems 102: 221–226) do not solve this problem. Here, we propose a method to calculate the multiple correlation and partial correlation for fuzzy data, by adopting the concepts from the multivariate correlation model. In order to fit into normal framework, we use empirical logit transform (see, Agresti, [1990, Categorical Data Analysis. New York: Wiley]; Johnson and Wichern, [1992, Applied Multivariate Statistical Analysis 3rd edn. Engelwood Cliffs; Prentice-Hall.]) for membership function grades to achieve this.
机译:在许多应用中,三个或更多模糊集的多重相关和部分相关非常重要,但是Chiang和Lin(1999,Fuzzy Sets and Systems 102:221-226)不能解决这个问题。在此,我们采用多元相关模型中的概念,提出了一种计算模糊数据的多重相关和偏相关的方法。为了适应正常框架,我们使用经验logit变换(请参阅Agresti,[1990,类别数据分析。纽约:Wiley]; Johnson and Wichern,[1992,应用多元统计分析,第三版,Engelwood Cliffs; Prentice- Hall。]),以实现会员资格等级。

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