A new class of high-dimensional partially linear varying coefficient model and its applications

This paper proposes a new method for solving a class of high-dimensional partially linear varying coefficient model. Firstly, an adaptive elastic net regularization term is added to the partially linear varying coefficient model to obtain a new model. This model improves the accuracy of the model by adjusting the parameter weights. Then, the ADMM method is used to solve the model parameters, and the convergence of the algorithm is analyzed. Subsequently, numerical simulations are conducted on high-dimensional datasets to demonstrate the effectiveness of the proposed method. Finally, the proposed method is applied to practical cases for testing and analysis, further verifying its effectiveness and application value.