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Graphical and formal statistical tools for the symmetry of bivariate copulas
Author(s) -
Quessy JeanFrançois,
Bahraoui Tarik
Publication year - 2013
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.1002/cjs.11193
Subject(s) - bivariate analysis , copula (linguistics) , null hypothesis , monte carlo method , asymmetry , statistical hypothesis testing , mathematics , computer science , statistics , population , contingency table , p value , econometrics , physics , demography , quantum mechanics , sociology
Statistical tools to check whether the underlying copula of a pair of random variables is symmetric are developed. The proposed methods are based on the theoretical and empirical versions of the C‐power functions introduced and formally studied by Bahraoui & Quessy (2013). On one part, a methodology is developed for testing the null hypothesis that the copula of a given population is symmetric. To this end, a sequential testing procedure is proposed where at each level, the P ‐value is estimated with the help of the multiplier bootstrap method. On another side, a related graphical method is proposed in order to gain an idea of the degree of asymmetry in bivariate data. The good properties of the methods in small samples are investigated with the help of Monte Carlo simulations under various scenarios of symmetric and asymmetric dependence. The newly introduced procedures are used to analyse the Nutrient and the Walker Lake data sets. The Canadian Journal of Statistics 41: 637–656; 2013 © 2013 Statistical Society of Canada