Empirical likelihood based variable selection for varying coefficient partially linear models with censored data. (English) Zbl 1299.62039
Summary: In this paper, we consider the variable selection for the parametric components of varying coefficient partially linear models with censored data. By constructing a penalized auxiliary vector ingeniously, we propose an empirical likelihood based variable selection procedure, and show that it is consistent and satisfies the sparsity. The simulation studies show that the proposed variable selection method is workable.
MSC:
62G08 | Nonparametric regression and quantile regression |
62G20 | Asymptotic properties of nonparametric inference |
62N02 | Estimation in survival analysis and censored data |
62J02 | General nonlinear regression |