Dependent wild bootstrap for the empirical process
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Leucht, Anne & Neumann, Michael H., 2013. "Dependent wild bootstrap for degenerate U- and V-statistics," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 257-280.
- Shao, Xiaofeng, 2010. "The Dependent Wild Bootstrap," Journal of the American Statistical Association, American Statistical Association, vol. 105(489), pages 218-235.
- Sharipov, Olimjon Sh. & Wendler, Martin, 2013. "Normal limits, nonnormal limits, and the bootstrap for quantiles of dependent data," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 1028-1035.
- Doukhan, Paul & Louhichi, Sana, 1999. "A new weak dependence condition and applications to moment inequalities," Stochastic Processes and their Applications, Elsevier, vol. 84(2), pages 313-342, December.
- Dehling, Herold & Wendler, Martin, 2010. "Central limit theorem and the bootstrap for U-statistics of strongly mixing data," Journal of Multivariate Analysis, Elsevier, vol. 101(1), pages 126-137, January.
- Shao, Xiaofeng, 2011. "A bootstrap-assisted spectral test of white noise under unknown dependence," Journal of Econometrics, Elsevier, vol. 162(2), pages 213-224, June.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Smeekes, S. & Urbain, J.R.Y.J., 2014. "A multivariate invariance principle for modified wild bootstrap methods with an application to unit root testing," Research Memorandum 008, Maastricht University, Graduate School of Business and Economics (GSBE).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Paul Doukhan & Gabriel Lang & Anne Leucht & Michael H. Neumann, 2015.
"Recent developments in bootstrap methods for dependent data,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 290-314, May.
- Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Michael Wolf & Dan Wunderli, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 352-376, May.
- Smeekes, S. & Urbain, J.R.Y.J., 2014. "A multivariate invariance principle for modified wild bootstrap methods with an application to unit root testing," Research Memorandum 008, Maastricht University, Graduate School of Business and Economics (GSBE).
- Hounyo, Ulrich & Varneskov, Rasmus T., 2020. "Inference for local distributions at high sampling frequencies: A bootstrap approach," Journal of Econometrics, Elsevier, vol. 215(1), pages 1-34.
- Hwang, Eunju & Shin, Dong Wan, 2012. "Strong consistency of the stationary bootstrap under ψ-weak dependence," Statistics & Probability Letters, Elsevier, vol. 82(3), pages 488-495.
- Jentsch, Carsten & Leucht, Anne, 2014. "Bootstrapping Sample Quantiles of Discrete Data," Working Papers 14-15, University of Mannheim, Department of Economics.
- Dehling, Herold & Sharipov, Olimjon Sh. & Wendler, Martin, 2015. "Bootstrap for dependent Hilbert space-valued random variables with application to von Mises statistics," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 200-215.
- Hounyo, Ulrich & Lahiri, Kajal, 2023.
"Estimating the variance of a combined forecast: Bootstrap-based approach,"
Journal of Econometrics, Elsevier, vol. 232(2), pages 445-468.
- Ulrich Hounyo & Kajal Lahiri, 2021. "Estimating the Variance of a Combined Forecast: Bootstrap-Based Approach," CREATES Research Papers 2021-14, Department of Economics and Business Economics, Aarhus University.
- Lea Wegner & Martin Wendler, 2024. "Robust change-point detection for functional time series based on U-statistics and dependent wild bootstrap," Statistical Papers, Springer, vol. 65(7), pages 4767-4810, September.
- Friedrich, Marina & Smeekes, Stephan & Urbain, Jean-Pierre, 2020.
"Autoregressive wild bootstrap inference for nonparametric trends,"
Journal of Econometrics, Elsevier, vol. 214(1), pages 81-109.
- Friedrich, Marina & Smeekes, Stephan & Urbain, Jean-Pierre, 2017. "Autoregressive Wild Bootstrap Inference for Nonparametric Trends," Research Memorandum 010, Maastricht University, Graduate School of Business and Economics (GSBE).
- Marina Friedrich & Stephan Smeekes & Jean-Pierre Urbain, 2018. "Autoregressive Wild Bootstrap Inference for Nonparametric Trends," Papers 1807.02357, arXiv.org, revised Nov 2019.
- Ulrich Hounyo & Rasmus T. Varneskov, 2018. "Inference for Local Distributions at High Sampling Frequencies: A Bootstrap Approach," CREATES Research Papers 2018-16, Department of Economics and Business Economics, Aarhus University.
- Denis Kojevnikov, 2021. "The Bootstrap for Network Dependent Processes," Papers 2101.12312, arXiv.org.
- Fu, Zhonghao & Hong, Yongmiao & Su, Liangjun & Wang, Xia, 2023. "Specification tests for time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 235(2), pages 720-744.
- Ulrich Hounyo, 2014. "The wild tapered block bootstrap," CREATES Research Papers 2014-32, Department of Economics and Business Economics, Aarhus University.
- Kaiji Motegi & Xiaojing Cai & Shigeyuki Hamori & Haifeng Xu, 2020. "Moving average threshold heterogeneous autoregressive (MAT‐HAR) models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1035-1042, November.
- Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Antoine Djogbenou & Sílvia Gonçalves & Benoit Perron, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 481-502, May.
- Hill, Jonathan B. & Motegi, Kaiji, 2019. "Testing the white noise hypothesis of stock returns," Economic Modelling, Elsevier, vol. 76(C), pages 231-242.
- Paulo M. D. C. Parente & Richard J. Smith, 2021.
"Quasi‐maximum likelihood and the kernel block bootstrap for nonlinear dynamic models,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 42(4), pages 377-405, July.
- Paulo M.D.C. Parente & Richard J. Smith, 2018. "Quasi-Maximum Likelihood and the Kernel Block Bootstrap for Nonlinear Dynamic Models," Working Papers REM 2018/59, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
- Paulo Parente & Richard J. Smith, 2019. "Quasi-maximum likelihood and the kernel block bootstrap for nonlinear dynamic models," CeMMAP working papers CWP60/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- El Ghouch, Anouar & Genton, Marc G. & Bouezmarni , Taoufik, 2012. "Measuring the Discrepancy of a Parametric Model via Local Polynomial Smoothing," LIDAM Discussion Papers ISBA 2012001, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Jerôme Dedecker & Paul Doukhan, 2002. "A New Covariance Inequality and Applications," Working Papers 2002-25, Center for Research in Economics and Statistics.
- Pierre Perron & Eduardo Zorita & Wen Cao & Clifford Hurvich & Philippe Soulier, 2017.
"Drift in Transaction-Level Asset Price Models,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 38(5), pages 769-790, September.
- Wen Cao & Clifford Hurvich & Philippe Soulier, 2012. "Drift in Transaction-Level Asset Price Models," Working Papers hal-00756372, HAL.
More about this item
Keywords
Absolute regularity ; bootstrap ; empirical process ; time series ; V -statistics ; quantiles ; Kolmogorov-Smirnov test;All these keywords.
JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2014-07-13 (Econometrics)
- NEP-ETS-2014-07-13 (Econometric Time Series)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mnh:wpaper:35246. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Katharina Rautenberg (email available below). General contact details of provider: https://edirc.repec.org/data/fvmande.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.