Title
Quantile curves and dependence structure for bivariate distributions
Abstract
Within the context of a general bivariate distribution an intuitive method is presented in order to study the dependence structure of the two distributions. A set of points-level curve-which accumulate the same probability for a fixed quadrant is considered. This procedure provides four level curves which can be considered as the boundary of a generalization of the real interquantile interval. It is shown that the accumulated probability among the level curves depends on the dependence structure of the distribution function where the dependence structure is given by the notion of copula. Furthermore, the case when the marginal distributions are independent is investigated. This result is used to find out positive or negative dependence properties for the variables. Finally, a nonparametric test for independence with a local dependence meaning is performed and applied to different data sets.
Year
DOI
Venue
2007
10.1016/j.csda.2006.08.017
Computational Statistics & Data Analysis
Keywords
Field
DocType
intuitive method,marginal distribution,general bivariate distribution,local dependence meaning,different data set,negative dependence property,fixed quadrant,dependence structure,distribution function,level curve,quantile curve,copula,nonparametric test,bivariate distribution
Econometrics,Joint probability distribution,Copula (linguistics),Nonparametric statistics,Probability distribution,Quantile,Bivariate analysis,Statistics,Distribution function,Marginal distribution,Mathematics
Journal
Volume
Issue
ISSN
51
10
Computational Statistics and Data Analysis
Citations 
PageRank 
References 
3
0.55
2
Authors
4
Name
Order
Citations
PageRank
Félix Belzunce1366.76
A. Castaño230.55
A. Olvera-Cervantes330.55
A. Suárez-Llorens4154.24