Strong convergence of sums of [alpha]-mixing random variables with applications to density estimation

In this paper we prove general statements on the strong convergence of sums of random variables belonging to a triangular array. We assume that this array satisfies an [alpha]-mixing condition. An inequality of Bernstein type is the crucial tool for the proofs. Moreover, some general results are applied to study the convergence of kernel density estimators.

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Year of publication:	1996
Authors:	Liebscher, Eckhard
Published in:	Stochastic Processes and their Applications. - Elsevier, ISSN 0304-4149. - Vol. 65.1996, 1, p. 69-80
Publisher:	Elsevier
Subject:	Strong convergence Triangular array \| [alpha]-mixing \| Kernel density estimators

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

Persistent link: https://www.econbiz.de/10008875354