Asymptotic normality of a wavelet estimator for asymptotically negatively associated errors

In this paper, we consider the nonparametric regression model Yni=g(ti)+εni,1≤i≤n and n≥1, where {ti} are non-random design points, and g(⋅) is an unknown Borel measurable function defined on [0, 1]. Under some general conditions, we study the asymptotic normality of the wavelet estimator of g(⋅), where the random errors {εni} are asymptotically negatively associated (ANA, for short) random variables. In addition, a simulation study is provided to evaluate the finite sample performance of the wavelet estimator.