Back to Search
Start Over
Bernstein estimator for unbounded copula densities
- Source :
- Statistics & risk modeling, 2013, Vol.30(4), pp.343-360 [Peer Reviewed Journal], Statistics and Risk Modeling with Applications in Finance and Insurance, Vol. 30, no.4, p. 343-360 (2013)
- Publication Year :
- 2013
- Publisher :
- Walter de Gruyter GmbH, 2013.
-
Abstract
- Copulas are widely used for modeling the dependence structure of multivariate data. Many methods for estimating the copula density functions are investigated. In this paper, we study the asymptotic properties of the Bernstein estimator for unbounded copula density functions. We show that the estimator converges to infinity at the corner and we establish its relative convergence when the copula density is unbounded. Also, we provide the uniform strong consistency of the estimator on every compact in the interior region. We investigate the finite sample performance of the estimator via an extensive simulation study and we compare the Bernstein copula density estimator with other nonparametric methods. Finally, we consider an empirical application where the asymmetric dependence between international equity markets (US, Canada, UK, and France) is examined.
- Subjects :
- Bernstein density copula estimator
Statistics and Probability
Multivariate statistics
Boundary bias
Relative convergence
Copula (linguistics)
boundary bias
Strong consistency
Nonparametric statistics
Estimator
Statistics::Other Statistics
Unbounded copula
Uniform strong consistency
Asymptotic properties
Modeling and Simulation
Consistent estimator
Econometrics
Statistics::Methodology
Applied mathematics
Statistics, Probability and Uncertainty
Minimax estimator
Nonparametric estimation
Mathematics
Subjects
Details
- ISSN :
- 21967040 and 21931402
- Volume :
- 30
- Database :
- OpenAIRE
- Journal :
- Statistics & Risk Modeling
- Accession number :
- edsair.doi.dedup.....72f61ae29c53becac7efe92ce7a05992
- Full Text :
- https://doi.org/10.1524/strm.2013.2003