Asymptotic results for the empirical process of stationary sequences

István I. Berkes; Siegfried Hörmann; Johannes Schauer

doi:10.1016/j.spa.2008.06.010

Asymptotic results for the empirical process of stationary sequences

István I. Berkes, Siegfried Hörmann, Johannes Schauer

Institute of Statistics (5060)

Research output: Contribution to journal › Article › peer-review

Abstract

We prove a strong invariance principle for the two-parameter empirical process of stationary sequences under a new weak dependence assumption. We give several applications of our results.

Original language	English
Pages (from-to)	1298-1324
Number of pages	27
Journal	Stochastic Processes and their Applications
Volume	119
Issue number	4
DOIs	https://doi.org/10.1016/j.spa.2008.06.010
Publication status	Published - 2009

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Basic - Fundamental (Grundlagenforschung)

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10.1016/j.spa.2008.06.010

Asymptotic Probability Theory
Schauer, J., Hörmann, S. & Berkes, I.
1/01/03 → …
Project: Research area

Cite this

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title = "Asymptotic results for the empirical process of stationary sequences",

abstract = "We prove a strong invariance principle for the two-parameter empirical process of stationary sequences under a new weak dependence assumption. We give several applications of our results.",

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doi = "10.1016/j.spa.2008.06.010",

language = "English",

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T1 - Asymptotic results for the empirical process of stationary sequences

AU - Berkes, István I.

AU - Hörmann, Siegfried

AU - Schauer, Johannes

PY - 2009

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N2 - We prove a strong invariance principle for the two-parameter empirical process of stationary sequences under a new weak dependence assumption. We give several applications of our results.

AB - We prove a strong invariance principle for the two-parameter empirical process of stationary sequences under a new weak dependence assumption. We give several applications of our results.

U2 - 10.1016/j.spa.2008.06.010

DO - 10.1016/j.spa.2008.06.010

M3 - Article

SN - 1879-209X

VL - 119

SP - 1298

EP - 1324

JO - Stochastic Processes and their Applications

JF - Stochastic Processes and their Applications

IS - 4

ER -

Asymptotic results for the empirical process of stationary sequences

Abstract

Treatment code (Nähere Zuordnung)

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Asymptotic Probability Theory

Cite this