Estimation and inference for dependence in multivariate data

Authors:
Olha Bodnar;Taras Bodnar;Arjun K. Gupta
Affiliations:
Department of Statistics, European University Viadrina, PO Box 1786, 15207 Frankfurt (Oder), Germany;Department of Statistics, European University Viadrina, PO Box 1786, 15207 Frankfurt (Oder), Germany;Department of Mathematics and Statistics, Bowling Green State University, Bowling Green, OH 43403, USA
Venue:
Journal of Multivariate Analysis
Year:
2010

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Abstract

In this paper, a new measure of dependence is proposed. Our approach is based on transforming univariate data to the space where the marginal distributions are normally distributed and then, using the inverse transformation to obtain the distribution function in the original space. The pseudo-maximum likelihood method and the two-stage maximum likelihood approach are used to estimate the unknown parameters. It is shown that the estimated parameters are asymptotical normally distributed in both cases. Inference procedures for testing the independence are also studied.