Pointwise convergence rates and central limit theorems for kernel density estimators in linear processes
Anton Schick and
Wolfgang Wefelmeyer
Statistics & Probability Letters, 2006, vol. 76, issue 16, 1756-1760
Abstract:
Convergence rates and central limit theorems for kernel estimators of the stationary density of a linear process have been obtained under the assumption that the innovation density is smooth (Lipschitz). We show that smoothness is not required. For example, it suffices that the innovation density has bounded variation.
Keywords: Lipschitz; continuity; Martingale; approximation; Smoothness; of; convolutions (search for similar items in EconPapers)
Date: 2006
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