A robust and efficient shrinkage-type variable selection procedure for varying Coefficient models is proposed, selection consistency and oracle properties are established. Furthermore, a BIC-type criterion is suggested for shrinkage parameter selection and theoretical property is discussed. Numerical studies and real data analysis also are included to illustrate the finite sample performance of our method.

中文翻译：

---

通过基于核的正则化秩回归对可变系数模型的变量选择

提出了一种适用于不同系数模型的稳健有效的收缩型变量选择程序，建立了选择一致性和预言机属性。此外，建议使用 BIC 类型标准来选择收缩参数，并讨论了理论性能。数值研究和真实数据分析也包括在内，以说明我们方法的有限样本性能。