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Fan Ruiya,Zhang Shuguang,Wu Yaohua 한국통계학회 2022 Journal of the Korean Statistical Society Vol.51 No.3
Based on functional relative errors, we develop a functional penalized smooth least absolute relative error (FPSLARE) criterion for locally sparse functional multiplicative regression models. Under some mild conditions, we establish the oracle properties of FPSLARE estimators, including the consistency of model selection and the asymptotic normality for the estimator. In addition, numerical studies and a real data analysis are carried out to evaluate the performance of the proposed approaches.