Abstract
The problem of choosing the best regressors to fit the circular regression data has not been addressed. We focus on the problem of finding the optimal regression-like equations (ORLE) in the Sarma and Jammalamadaka (SJ) circular regression model (Sarma and Jammalamadaka 1993). First, the issues of under-fitting and over-fitting of regression equations in the SJ model are addressed. Then, we extend Mallows’ \(C_p\) and AIC and their robust versions to the SJ circular regression model. A simulation study is used to investigate the performance of the proposed criteria. Results showed that robust circular Mallows’ \(C_p\) and AIC are effective in selecting an accurate ORLE for circular regression models in both the clean and contaminated data sets. An application of the proposed procedures is discussed using a real medical data set.
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Alshqaq, S.S., Abuzaid, A.H. & Ahmadini, A.A. Selection of Optimal Regression-like Equations for Circular Regression Model via Mallows’ \(C_p\) and AIC Criteria. Iran J Sci 47, 531–543 (2023). https://doi.org/10.1007/s40995-023-01420-y
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DOI: https://doi.org/10.1007/s40995-023-01420-y