Investigation of the characteristics and estimation of quantities of hidden and hard-to-access population are of interest to scientists. Such populations are difficult to target because of their elusive nature or other prohibitive characteristics. So crafting designs of a representative sample...

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....

Nonparametric regression models have been used to explorefeatures of data. Various estimation procedures have been proposedfor estimating nonparametric regression models in the literature.The existing procedures may enjoy some statistically optimalproperties, but it is difficult to use the...

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...