Dependent wild bootstrap for the empirical process

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

Working Papers from University of Mannheim, Department of Economics

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.

Keywords: Absolute regularity; bootstrap; empirical process; time series; V -statistics; quantiles; Kolmogorov-Smirnov test (search for similar items in EconPapers)
JEL-codes: C14 (search for similar items in EconPapers)
Date: 2014
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://madoc.bib.uni-mannheim.de/35246/4/Doukhan% ... 2C_Neumann_14-01.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:mnh:wpaper:35246

Access Statistics for this paper

More papers in Working Papers from University of Mannheim, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Katharina Rautenberg ().