Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5129287 | Journal of the Korean Statistical Society | 2017 | 11 Pages |
Abstract
Nonparametric estimation of conditional copulas with one parameter has been investigated in Acar et al. (2011). The estimation for multivariate multiparameter conditional copulas, however, has not been considered so far. This paper adopts the local linear smoothing technique and Newton-Raphson method to estimate those copulas. Under some regularity conditions, the asymptotic normality of the estimators is obtained. Simulation work shows the efficiency of the proposed method. As an application, we analyze a life expectancies data set and show that the conditional t copula outperforms the conditional Clayton, Frank and Gumbel copulas.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Jin-Guan Lin, Kong-Sheng Zhang, Yan-Yong Zhao,