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Multivariate Least Squares Regression using Interval-Valued Fuzzy Data and based on Extended Yao-Wu Signed Distance

机译:使用间隔值模糊数据进行多变量最小二乘回归,并基于扩展yao-wu符号距离

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摘要

The purpose of this study is to introduce a new regression model, based on the least squares method, when the available data of both explanatory variable(s) and response variable are interval-valued fuzzy (IVF) numbers. The proposed method is based on a new metric on the space of IVF numbers, which is an extended version of the signed distance introduced by Yao and Wu (2000). In order to evaluate the goodness of fit of the proposed model, we introduce some new indices based on the similarity measure and the coefficient of multiple determination. Finally, the application of proposed approach is provided to model some real data.
机译:本研究的目的是引入基于最小二乘法的新回归模型,当解释变量和响应变量的可用数据是间隔值模糊(IVF)编号时。该方法基于IVF数字空间的新度量,这是姚明和吴(2000)引入的符号距离的扩展版本。为了评估所提出的模型的良好性,我们根据相似度测量和多重测定系数介绍一些新的指标。最后,提供了建议方法的应用来模拟一些实际数据。

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