B0790
Title: A copula model for multivariate circular data
Authors: Christophe Ley - University of Luxembourg (Luxembourg) [presenting]
Shogo Kato - Institute of Statistical Mathematics (Japan)
Abstract: A new family of distributions is proposed for multivariate circular data. The focus first lies on the trivariate case. Its density can be expressed in simple form without involving infinite sums or integrals. The univariate marginals of the proposed distributions are the uniform distributions on the circle, and therefore the presented family is considered a copula. The bivariate marginals of the proposed distributions are members of the Wehrly-Johnson family. The univariate and bivariate conditional distributions are also well-known in the literature. An efficient algorithm to generate random variates from our model is presented, trigonometric moments, as well as other appealing properties, are given, and maximum likelihood estimation for the presented distributions is considered. Finally, an extension of the proposed family for multivariate circular data is considered.
