本研究考慮迴歸模型架構下的變數選取問題，提出一種基於 copula entropy 的檢定，用以檢測模型中是否需要納入新的解釋變數。基於此檢定，建構一種逐步向前變數選取演算法，透過模擬實驗結果顯示，本方法在非線性問題中具有良好的選取表現，可以作為非線性模型中的一種非參數選取工具。

This study addresses the problem of variable selection within the framework of regression models. A novel test based on copula entropy is proposed to assess whether additional explanatory variables should be included in the model. Based on this test, a forward stepwise variable selection algorithm is constructed. Simulation results show that the proposed method performs well in nonlinear settings, suggesting its potential as a nonparametric variable selection tool for complex nonlinear modeling scenarios.

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