@article { ISI:000327908200006,
	title = {Geometric interpretation of the residual dependence coefficient},
	journal = {JOURNAL OF MULTIVARIATE ANALYSIS},
	volume = {123},
	year = {2014},
	month = {JAN},
	pages = {85-95},
	publisher = {ELSEVIER INC},
	type = {Article},
	address = {525 B STREET, STE 1900, SAN DIEGO, CA 92101-4495 USA},
	abstract = {The residual dependence coefficient was originally introduced by Ledford and Tawn (1996) [25] as a measure of residual dependence between extreme values in the presence of asymptotic independence. We present a geometric interpretation of this coefficient with the additional assumptions that the random samples from a given distribution can be scaled to converge onto a limit set and that the marginal distributions have Weibull-type tails. This result leads to simple and intuitive computations of the residual dependence coefficient for a variety of distributions. (C) 2013 Elsevier Inc. All rights reserved.},
	keywords = {Asymptotic independence, Geometric approach, Limit set, Multivariate density, Residual dependence coefficient, Sample clouds},
	issn = {0047-259X},
	doi = {10.1016/j.jmva.2013.08.018},
	author = {Nolde, Natalia}
}
