New Techniques for Empirical Process of Dependent Data

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dc.creatorDehling, Herold
dc.creatorDurieu, Olivier
dc.creatorVolný, Dalibor
dc.date2008-06-18
dc.date2008-10-01
dc.date.accessioned2026-07-07T10:06:18Z
dc.date.available2026-07-07T10:06:18Z
dc.descriptionWe present a new technique for proving empirical process invariance principle for stationary processes $(X_n)_{n\geq 0}$. The main novelty of our approach lies in the fact that we only require the central limit theorem and a moment bound for a restricted class of functions $(f(X_n))_{n\geq 0}$, not containing the indicator functions. Our approach can be applied to Markov chains and dynamical systems, using spectral properties of the transfer operator. Our proof consists of a novel application of chaining techniques.
dc.identifierhttps://arxiv.org/abs/0806.2941
dc.identifierhttp://arxiv.org/abs/0806.2941
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/170281
dc.subjectProbability
dc.subjectStatistics Theory
dc.subject60G10; 60F17; 62G30
dc.titleNew Techniques for Empirical Process of Dependent Data
dc.typetext

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