In this dissertation, several new statistical procedures in nonparametric and semiparametric models are proposed. The concerns of the research are efficiency, robustness and sparsity.In Chapter 3, we propose complete composite quantile regression (CQR) procedures for estimating both the...

Nonparametric function estimation via local polynomial regression has been widely studied in the literature, especially in the past two decades. In practice, we confront two challenges. Firstly, the local least squares estimator may not be the best choice when errors are heavily tailed....

Motivated by an empirical analysis of a data set collected in the field of ecology, we proposed nonlinear varying-coefficient models, a new class of varying-coefficient models. We further propose an estimation procedure for the nonlinear varying-coefficient models by using local linear...