title: NON-PARAMETRIC ESTIMATION UNDER STRONG DEPENDENCE.
abstract: We study non-parametric regression function estimation for models with strong dependence. Compared with short-range dependent models, long-range dependent models often result in slower convergence rates. We propose a simple differencing-sequence based non-parametric estimator that achieves the same convergence rate as if the data were independent. Simulation studies show that the proposed method has good finite sample performance.
authors.affiliation: Penn State University.
authors.forename: Zhibiao
authors.initials: Z
authors.lastname: Zhao
authors.affiliation: Novartis Oncology.
authors.forename: Yiyun
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Penn State University.
authors.forename: Runze
authors.initials: R
authors.lastname: Li
keywords: Differencing; long-range dependence; non-parametric regression; short-range dependence; time series