Affiliations: Department of Statistics, Faculty of Mathematical Sciences and Statistics, University of Birjand, Birjand, Iran
Correspondence:
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Corresponding author. Mohsen Arefi, Department of Statistics, Faculty of Mathematical Sciences and Statistics,
University of Birjand, Birjand, Iran. Tel.: +98 56 32202301; Fax: +98 56 32202041; E-mail: Arefi@birjand.ac.ir.
Abstract: In this paper, a new approach is presented to the problem of the clustering regression models with imprecise quantities. In this approach, the response variable and the parameters of model are assumed to be the interval-valued fuzzy numbers. We introduce two indices to investigate the goodness-of-fit of such models based on the similarity measure and the squared errors. In addition to, the predictive ability of the proposed clustering models is evaluated by using the cross-validation method. Finally, the application of the proposed approach in modeling some soil characteristics is studied.
Keywords: Clustering regression, cross-validation, goodness of fit, interval-valued fuzzy set, least squares method, similarity measure
