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Wang, Y. and Woodroofe, M. (2014) On the Asymptotic Normality of Kernel Density Estimators for Causal Linear Random Fields. Journal of Multivariate Analysis, 123, 201-213.
https://doi.org/10.1016/j.jmva.2013.09.008

has been cited by the following article:

• TITLE: The Rate of Asymptotic Normality of Frequency Polygon Density Estimation for Spatial Random Fields

  AUTHORS: Shanchao Yang, Xin Yang, Guodong Xing, Yongming Li

  KEYWORDS: Frequency Polygon, Berry-Esseen Bound, Rate of Asymptotic Normality, Mixing Random Field

  JOURNAL NAME: Open Journal of Statistics, Vol.8 No.6, December 29, 2018

  ABSTRACT: This paper is to investigate the convergence rate of asymptotic normality of frequency polygon estimation for density function under mixing random fields, which include strongly mixing condition and some weaker mixing conditions. A Berry-Esseen bound of frequency polygon is established and the convergence rates of asymptotic normality are derived. In particularly, for the optimal bin width , it is showed that the convergence rate of asymptotic normality reaches to when mixing coefficient tends to zero exponentially fast.