Bootstrap in moving average models
Author
Abstract
Suggested Citation
DOI: 10.1007/BF02481148
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Hai‐Bin Wang, 2008. "Nonlinear ARMA models with functional MA coefficients," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(6), pages 1032-1056, November.
- Thiago R. Santos & Glaura C. Franco & Dani Gamerman, 2010. "Comparison of Classical and Bayesian Approaches for Intervention Analysis," International Statistical Review, International Statistical Institute, vol. 78(2), pages 218-239, August.
- Gonzalo Camba-Mendez & George Kapetanios, 2002.
"Bootstrap Statistical Tests of Rank Determination for System Identification,"
Working Papers
468, Queen Mary University of London, School of Economics and Finance.
- Gonzalo Camba-Mendez & George Kapetanios, 2002. "Bootstrap Statistical Tests of Rank Determination for System Identification," Working Papers 468, Queen Mary University of London, School of Economics and Finance.
- Moon, Seongman & Velasco, Carlos, 2013.
"Tests for m-dependence based on sample splitting methods,"
Journal of Econometrics, Elsevier, vol. 173(2), pages 143-159.
- Seongman Moon & Carlos Velasco, 2011. "Tests for m-dependence Based on Sample Splitting Methods," Working Papers 1108, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
- Blake, Andrew P. & Kapetanios, George, 2000.
"A radial basis function artificial neural network test for ARCH,"
Economics Letters, Elsevier, vol. 69(1), pages 15-23, October.
- Andrew Blake, 1999. "A Radial Basis Function Artificial Neural Network Test for ARCH," National Institute of Economic and Social Research (NIESR) Discussion Papers 154, National Institute of Economic and Social Research.
- Alonso Fernández, Andrés Modesto & Peña, Daniel & Romo, Juan, 2000. "Resampling time series by missing values techniques," DES - Working Papers. Statistics and Econometrics. WS 9923, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Wang, Bin & Zheng, Xu, 2022. "Testing for the presence of jump components in jump diffusion models," Journal of Econometrics, Elsevier, vol. 230(2), pages 483-509.
- Jeremy Berkowitz & Lutz Kilian, 2000.
"Recent developments in bootstrapping time series,"
Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 1-48.
- Jeremy Berkowitz & Lutz Kilian, "undated". "Recent Developments in Bootstrapping Time Series," Finance and Economics Discussion Series 1996-45, Board of Governors of the Federal Reserve System (U.S.), revised 10 Dec 2019.
- Jeremy Berkowitz & Lutz Kilian, 1996. "Recent developments in bootstrapping time series," Finance and Economics Discussion Series 96-45, Board of Governors of the Federal Reserve System (U.S.).
- Jinyong Hahn & Zhipeng Liao, 2021. "Bootstrap Standard Error Estimates and Inference," Econometrica, Econometric Society, vol. 89(4), pages 1963-1977, July.
- Joel L. Horowitz, 2018. "Bootstrap Methods in Econometrics," Papers 1809.04016, arXiv.org.
- Datta, Somnath, 1995. "Limit theory and bootstrap for explosive and partially explosive autoregression," Stochastic Processes and their Applications, Elsevier, vol. 57(2), pages 285-304, June.
- Härdle, Wolfgang & Horowitz, Joel L. & Kreiss, Jens-Peter, 2001. "Bootstrap methods for time series," SFB 373 Discussion Papers 2001,59, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Wolfgang Härdle & Joel Horowitz & Jens‐Peter Kreiss, 2003. "Bootstrap Methods for Time Series," International Statistical Review, International Statistical Institute, vol. 71(2), pages 435-459, August.
- Joel L. Horowitz, 2018. "Bootstrap methods in econometrics," CeMMAP working papers CWP53/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
More about this item
Keywords
Moving average models; stationary autoregressions; Cramer's condition; Edgeworth expansions; empirical distribution function; bootstrap;All these keywords.
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:spr:aistmt:v:42:y:1990:i:4:p:753-768. 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.
We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.