On Comparing and Classifying Several Independent Linear and Non-Linear Regression Models with Symmetric Errors

Baleanu, DumitruPan, Ji-JunMahmoudi, Mohammad RezaBaleanu, DumitruMaleki, Mohsen2020-03-272020-03-272019Pan, Ji-Jun...et al. (2019). "On Comparing and Classifying Several Independent Linear and Non-Linear Regression Models with Symmetric Errors", Symmetry-Basel, Vol. 11, No. 6.2073-8994https://hdl.handle.net/20.500.12416/2763In 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.eninfo:eu-repo/semantics/openAccessComparisonFriedman TestLinear RegressionNonlinear RegressionSign TestSymmetric ErrorsWilcoxon TestOn Comparing and Classifying Several Independent Linear and Non-Linear Regression Models with Symmetric ErrorsOn Comparing and Classifying Several Independent Linear and Non-Linear Regression Models With Symmetric ErrorsArticle11610.3390/sym11060820