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Regression model for interval-valued variables based on copulas

机译:基于copulas的区间值变量回归模型

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摘要

In real problems, it is usual to have the available data presented as intervals. Therefore, different approaches have been proposed to obtain a regression model for this new type of data. In this paper, we represent the interval-valued response variable as a bivariate random vector and we consider the copula's theory to propose a general bivariate distribution for Z, creating a more flexible random component to the model. Inference techniques and a residual definition based on deviance are considered, as well as applications to synthetic and real data sets that demonstrate the usefulness of the proposed approach. The new method is also compared with other methods reported in the literature.
机译:在实际问题中,通常将可用数据显示为间隔。因此,已经提出了不同的方法来获得这种新型数据的回归模型。在本文中,我们将区间值响应变量表示为双变量随机向量,并考虑copula的理论为Z提出一般的双变量分布,从而为模型创建了更灵活的随机分量。考虑了基于偏差的推理技术和残差定义,以及对合成和真实数据集的应用,这些数据证明了所提出方法的有效性。还将该新方法与文献中报道的其他方法进行了比较。

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