Asymptotic properties of the Bernstein density copula for dependent data
AbstractCopulas are extensively used for dependence modeling. In many cases the data does not reveal how the dependence can be modeled using a particular parametric copula. Nonparametric copulas do not share this problem since they are entirely data based. This paper proposes nonparametric estimation of the density copula for α-mixing data using Bernstein polynomials. We study the asymptotic properties of the Bernstein density copula, i.e., we provide the exact asymptotic bias and variance, we establish the uniform strong consistency and the asymptotic normality.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2008045.
Date of creation: 01 Jul 2008
Date of revision:
Contact details of provider:
Postal: Voie du Roman Pays 34, 1348 Louvain-la-Neuve (Belgium)
Fax: +32 10474304
Web page: http://www.uclouvain.be/core
More information through EDIRC
nonparametric estimation; copula; Bernstein polynomial; α-mixing; asymptotic properties; boundary bias;
Other versions of this item:
- Bouezmarni, Taoufik & Rombouts, Jeroen V. K. & Taamouti, Abderrahim, . "Asymptotic properties of the Bernstein density copula for dependent data," Open Access publications from Universidad Carlos III de Madrid info:hdl:10016/2733, Universidad Carlos III de Madrid.
- Taoufik Bouezmarni & Jeroen V. K. Rombouts & Abderrahim Taamouti, 2008. "Asymptotic properties of the Bernstein density copula for dependent data," Economics Working Papers we083619, Universidad Carlos III, Departamento de Economía.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation of copula-based semiparametric time series models," Journal of Econometrics, Elsevier, vol. 130(2), pages 307-335, February.
- Chen, Xiaohong & Fan, Yanqin & Tsyrennikov, Viktor, 2006.
"Efficient Estimation of Semiparametric Multivariate Copula Models,"
Journal of the American Statistical Association,
American Statistical Association, vol. 101, pages 1228-1240, September.
- Xiaohong Chen & Yanqin Fan & Victor Tsyrennifov, 2004. "Efficient Estimation of Semiparametric Multivariate Copula Models," Vanderbilt University Department of Economics Working Papers 0420, Vanderbilt University Department of Economics.
- Joe, Harry, 2005. "Asymptotic efficiency of the two-stage estimation method for copula-based models," Journal of Multivariate Analysis, Elsevier, vol. 94(2), pages 401-419, June.
- Sancetta, Alessio & Satchell, Stephen, 2004. "The Bernstein Copula And Its Applications To Modeling And Approximations Of Multivariate Distributions," Econometric Theory, Cambridge University Press, vol. 20(03), pages 535-562, June.
- Axel Tenbusch, 1997. "Nonparametric curve estimation with bernstein estimates," Metrika, Springer, vol. 45(1), pages 1-30, January.
- Yoshihide Kakizawa, 2006. "Bernstein polynomial estimation of a spectral density," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(2), pages 253-287, 03.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Alain GILLIS).
If references are entirely missing, you can add them using this form.