Ordinary least-square (OLS) estimators for a linear model are very sensitive to unusual
values in the design space or outliers among y values. Even one single atypical value may …

We study the efficient estimation of nonparametric regression in the presence of
heteroskedasticity. We focus our analysis on local polynomial estimation of nonparametric …

This article studies the generalized method of moment estimation of semiparametric varying
coefficient partially linear spatial autoregressive model. The technique of profile least …

High dimensionality has been a significant feature in modern statistical modeling. Sufficient
dimension reduction (SDR) as an efficient tool aims at reducing the original high …

Issues concerning spatial dependence among cross-sectional units in econometrics have
received more and more attention, while in statistical modeling, rarely can the analysts have …

In this paper, we propose a two step estimation procedure to improve estimation efficiency of
the index coefficients and unknown functions. Specifically, in the first step, we obtain the …

Issues concerning spatial dependence among cross-sectional units in econometrics have
received more and more attention. Motivated by a Boston housing price data analysis, this …

An information cascade occurs when a person observes the actions of others and then
engages in the same acts. Cascades may break out if a large population of nodes in the …

The varying coefficient model is a potent dimension reduction tool for nonparametric
modeling and has received extensive attention from researchers. Most existing methods for …

In this paper, a new adaptive estimation approach is proposed for the spatially varying
coefficient models with unknown error distribution, unlike geographically weighted …