基于众数回归的变系数模型统一变量选择

研究了众数回归下变系数模型的统一变量选择问题.利用B样条基函数近似非参数部分,在众数回归下建立SCAD惩罚函数同时选择变系数模型中的重要变量并且识别具有常数效应的协变量,在一定条件下, 证明惩罚估计量相合性和稀疏性,通过数值模拟评估所提出的变量选择方法的有效性.

A unified variable selection approach forvarying coefficient models based modal regression

A unified variable selection invarying coefficient model with modal regressionis studied. B spline basis function is adopted to approximate the nonparametric part, and SCAD penalty function is established under modal regression. The proposed procedure using SCAD penalty function to select important variables simultaneously for the varying coefficient model can also identify the covariates with constant effects. Under certain conditions, the concoherence and sparseness of penalty estimation are proved. Finally, the effectiveness of the proposed variable selection method is evaluated by numerical simulation.