Pointwise convergence rates and central limit theorems for kernel density estimators in linear processes

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.

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Year of publication:	2006
Authors:	Schick, Anton ; Wefelmeyer, Wolfgang
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 76.2006, 16, p. 1756-1760
Publisher:	Elsevier
Keywords:	Lipschitz continuity Martingale approximation Smoothness of convolutions

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005313965