Optimizing the smoothed bootstrap
Author
Abstract
Suggested Citation
DOI: 10.1007/BF00773412
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Jones, M. C., 1991. "On correcting for variance inflation in kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 11(1), pages 3-15, January.
- Jones, M. C. & Sheather, S. J., 1991. "Using non-stochastic terms to advantage in kernel-based estimation of integrated squared density derivatives," Statistics & Probability Letters, Elsevier, vol. 11(6), pages 511-514, June.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Alexandre Leblanc, 2009. "Chung–Smirnov property for Bernstein estimators of distribution functions," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(2), pages 133-142.
- Hotta, Luiz & Trucíos, Carlos, 2015. "Robust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws1523, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
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.- José E. Chacón & Carlos Tenreiro, 2012. "Exact and Asymptotically Optimal Bandwidths for Kernel Estimation of Density Functionals," Methodology and Computing in Applied Probability, Springer, vol. 14(3), pages 523-548, September.
- Mokkadem, Abdelkader & Pelletier, Mariane, 2020. "Online estimation of integrated squared density derivatives," Statistics & Probability Letters, Elsevier, vol. 166(C).
- J. Liao & Yujun Wu & Yong Lin, 2010. "Improving Sheather and Jones’ bandwidth selector for difficult densities in kernel density estimation," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(1), pages 105-114.
- Hall, Peter & Wolff, Rodney C. L., 1995. "Estimators of integrals of powers of density derivatives," Statistics & Probability Letters, Elsevier, vol. 24(2), pages 105-110, August.
- Rudolf Grübel, 1994. "Estimation of density functionals," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 46(1), pages 67-75, March.
- T. Sclocco & M. Marzio, 2001. "A note on kernel density estimation for non-negative random variables," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 10(1), pages 67-79, January.
- Fabian Krüger & Sebastian Lerch & Thordis Thorarinsdottir & Tilmann Gneiting, 2021. "Predictive Inference Based on Markov Chain Monte Carlo Output," International Statistical Review, International Statistical Institute, vol. 89(2), pages 274-301, August.
- Moreira, C. & Van Keilegom, I., 2013. "Bandwidth selection for kernel density estimation with doubly truncated data," Computational Statistics & Data Analysis, Elsevier, vol. 61(C), pages 107-123.
- Christopher Withers & Saralees Nadarajah, 2011. "Nonparametric confidence intervals for the integral of a function of an unknown density," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(4), pages 943-966.
- Sidibé, I.B. & Khatab, A. & Diallo, C. & Adjallah, K.H., 2016. "Kernel estimator of maintenance optimization model for a stochastically degrading system under different operating environments," Reliability Engineering and System Safety, Elsevier, vol. 147(C), pages 109-116.
- Gonzalez-Manteiga, W. & Sanchez-Sellero, C. & Wand, M. P., 1996. "Accuracy of binned kernel functional approximations," Computational Statistics & Data Analysis, Elsevier, vol. 22(1), pages 1-16, June.
- Powell, James L. & Stoker, Thomas M., 1996.
"Optimal bandwidth choice for density-weighted averages,"
Journal of Econometrics, Elsevier, vol. 75(2), pages 291-316, December.
- Powell, James L. & Stoker, Thomas M., 1992. "Optimal bandwidth choice for density-weighted averages," Working papers 3424-92., Massachusetts Institute of Technology (MIT), Sloan School of Management.
- Wang, Qing & Lindsay, Bruce G., 2015. "Improving cross-validated bandwidth selection using subsampling-extrapolation techniques," Computational Statistics & Data Analysis, Elsevier, vol. 89(C), pages 51-71.
- Filippone, Maurizio & Sanguinetti, Guido, 2011. "Approximate inference of the bandwidth in multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3104-3122, December.
- Saavedra, Ángeles & Cao, Ricardo, 1999. "Rate of convergence of a convolution-type estimator of the marginal density of a MA(1) process," Stochastic Processes and their Applications, Elsevier, vol. 80(2), pages 129-155, April.
- Hidehiko Ichimura & Oliver Linton, 2001.
"Asymptotic expansions for some semiparametric program evaluation estimators,"
CeMMAP working papers
04/01, Institute for Fiscal Studies.
- Hidehiko Ichimura & Oliver Linton, 2003. "Asymptotic Expansions for Some Semiparametric Program Evaluation Estimators," STICERD - Econometrics Paper Series 451, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Hidehiko Ichimura & Oliver Linton, 2001. "Asymptotic expansions for some semiparametric program evaluation estimators," CeMMAP working papers CWP04/01, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Ichimura, Hidehiko & Linton, Oliver, 2003. "Asymptotic expansions for some semiparametric program evaluation estimators," LSE Research Online Documents on Economics 2098, London School of Economics and Political Science, LSE Library.
- Farmen, Mark & Marron, J. S., 1999. "An assessment of finite sample performance of adaptive methods in density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 30(2), pages 143-168, April.
- Dimitrios Bagkavos, 2011. "Local linear hazard rate estimation and bandwidth selection," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(5), pages 1019-1046, October.
- M. Jones & I. McKay & T. Hu, 1994. "Variable location and scale kernel density estimation," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 46(3), pages 521-535, September.
- Gael FOKAM & Christelle MAPA & Mathurin ISSABE, 2021. "Energy intensity and industrialization in Cameroon," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 5(11), pages 57-67, November.
More about this item
Keywords
Bootstrap; functional estimation; kernel density estimation; mean integrated squared error; mean squared error; quantile; rescaling; smoothing;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:47:y:1995:i:1:p:65-80. 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: 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.