Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Article Citation - Scopus: 47On Comparing and Classifying Several Independent Linear and Non-Linear Regression Models With Symmetric Errors(MDPI AG, 2019) Mahmoudi, M.R.; Baleanu, D.; Maleki, M.; Ji-jun, P.In many real world problems, science fields such as biology, computer science, data mining, electrical and mechanical engineering, and signal processing, researchers aim to compare and classify several regression models. In this paper, a computational approach, based on the non-parametric methods, is used to investigate the similarities, and to classify several linear and non-linear regression models with symmetric errors. The ability of each given approach is then evaluated using simulated and real world practical datasets. © 2019 by the authors.