Logo of Humboldt-Universität zu BerlinLogo of Humboldt-Universität zu Berlin
edoc-Server
Open-Access-Publikationsserver der Humboldt-Universität
de|en
Header image: facade of Humboldt-Universität zu Berlin
View Item 
  • edoc-Server Home
  • Schriftenreihen und Sammelbände
  • Fakultäten und Institute der HU
  • Wirtschaftswissenschaftliche Fakultät
  • Discussion papers of interdisciplinary research project 373 / Sonderforschungsbereich 373
  • View Item
  • edoc-Server Home
  • Schriftenreihen und Sammelbände
  • Fakultäten und Institute der HU
  • Wirtschaftswissenschaftliche Fakultät
  • Discussion papers of interdisciplinary research project 373 / Sonderforschungsbereich 373
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.
All of edoc-ServerCommunity & CollectionTitleAuthorSubjectThis CollectionTitleAuthorSubject
PublishLoginRegisterHelp
StatisticsView Usage Statistics
All of edoc-ServerCommunity & CollectionTitleAuthorSubjectThis CollectionTitleAuthorSubject
PublishLoginRegisterHelp
StatisticsView Usage Statistics
View Item 
  • edoc-Server Home
  • Schriftenreihen und Sammelbände
  • Fakultäten und Institute der HU
  • Wirtschaftswissenschaftliche Fakultät
  • Discussion papers of interdisciplinary research project 373 / Sonderforschungsbereich 373
  • View Item
  • edoc-Server Home
  • Schriftenreihen und Sammelbände
  • Fakultäten und Institute der HU
  • Wirtschaftswissenschaftliche Fakultät
  • Discussion papers of interdisciplinary research project 373 / Sonderforschungsbereich 373
  • View Item
2006-02-02Buch DOI: 10.18452/3748
A Nonparametric Test for the Stationary Density
Neumann, Michael H.
Paparoditis, Efstathios
We propose a nonparametric test for checking parametric hypotheses about the stationary density of weakly dependent observations. The test statistic is based on the L2-distance between a nonparametric and a smoothed version of a parametric estimate of the stationary density. It can be shown that this statistic behaves asymptotically as in the case of independent observations. Accordingly, we propose an i.i.d.-type bootstrap to determine the critical value for the test.
Files in this item
Thumbnail
58.pdf — Adobe PDF — 260.4 Kb
MD5: 7a4c89c7c4d4bc3f9cf268673fb29b97
Cite
BibTeX
EndNote
RIS
InCopyright
Details
DINI-Zertifikat 2019OpenAIRE validatedORCID Consortium
Imprint Policy Contact Data Privacy Statement
A service of University Library and Computer and Media Service
© Humboldt-Universität zu Berlin
 
DOI
10.18452/3748
Permanent URL
https://doi.org/10.18452/3748
HTML
<a href="https://doi.org/10.18452/3748">https://doi.org/10.18452/3748</a>