Journal
STATISTICS
Volume 49, Issue 3, Pages 497-521Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/02331888.2014.932792
Keywords
Primary: 62G05; Secondary: 62G20; Archimedean copulas; multivariate L-moments; parametric estimation; copulas; FGM copulas; dependence
Categories
Ask authors/readers for more resources
Serfling and Xiao [A contribution to multivariate L-moments, L-comoment matrices. J Multivariate Anal. 2007;98:1765-1781] extended the L-moment theory to the multivariate setting. In the present paper, we focus on the two-dimensional random vectors to establish a link between the bivariate L-moments (BLM) and the underlying bivariate copula functions. This connection provides a new estimate of dependence parameters of bivariate statistical data. Extensive simulation study is carried out to compare estimators based on the BLM, the maximum likelihood, the minimum distance and a rank approximate Z-estimation. The obtained results show that, when the sample size increases, BLM-based estimation performs better as far as the bias and computation time are concerned. Moreover, the root-mean-squared error is quite reasonable and less sensitive in general to outliers than those of the above cited methods. Further, the proposed BLM method is an easy-to-use tool for the estimation of multiparameter copula models. A generalization of the BLM estimation method to the multivariate case is discussed.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available