Dependent wild bootstrap for the empirical process


Doukhan, Paul ; Lang, Gabriel ; Leucht, Anne ; Neumann, Michael H.


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URL: https://ub-madoc.bib.uni-mannheim.de/35246
URN: urn:nbn:de:bsz:180-madoc-352468
Document Type: Working paper
Year of publication: 2014
The title of a journal, publication series: Working Paper Series
Volume: 14-01
Place of publication: Mannheim
Publication language: English
Institution: School of Law and Economics > VWL, Theoretische Ökonometrie u. Statistik (Juniorprofessur) (Leucht 2012-2014)
MADOC publication series: Department of Economics > Working Paper Series
Subject: 330 Economics
Classification: JEL: C14,
Keywords (English): Absolute regularity , bootstrap , empirical process , time series , V -statistics , quantiles , Kolmogorov-Smirnov test
Abstract: In this paper, we propose a model-free bootstrap method for the empirical process under absolute regularity. More precisely, consistency of an adapted version of the so-called dependent wild bootstrap, that was introduced by Shao (2010) and is very easy to implement, is proved under minimal conditions on the tuning parameter of the procedure. We apply our results to construct confidence intervals for unknown parameters and to approximate critical values for statistical tests. A simulation study shows that our method is competitive to standard block bootstrap methods in finite samples.




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