On the asymptotic normality of kernel density estimators for causal linear random fields

Yizao Wang and Michael Woodroofe

Journal of Multivariate Analysis, 2014, vol. 123, issue C, 201-213

Abstract: We establish sufficient conditions for the asymptotic normality of kernel density estimators applied to causal linear random fields, by m-dependent approximation. Our conditions on the coefficients of linear random fields are weaker than the known results, although our assumption on the bandwidth is not minimal. We also establish a convergence rate of Berry–Esseen’s type.

Keywords: Central limit theorem; Causal linear random field; Kernel density estimation; m-dependence; Moment inequality (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1016/j.jmva.2013.09.008

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