Abstract
A modification of a test for independence based on the empirical characteristic function is investigated. The initial test is not consistent in the general case. The modification makes the test always consistent and asymptotically distribution free. It is based on a special transformation of the data.
Similar content being viewed by others
References
J. R. Blum, J. Kiefer, and M. Rosenblatt, “Distribution free tests of independence based on the sample distribution function,”Ann. Math. Statist.,32, 485–498 (1961).
S. Csörgő, “Limit behavior of the empirical characteristic function,”Ann. Probab.,9, No. 1, 130–144 (1981).
S. Csörgő, “Multivariate empirical characteristic functions,”Z. Wahrscheinlichkeitstheorie verw. Gebiete.,55, 203–229 (1981).
S. Csörgő, “Testing for independence by the empirical characteristic function,”J. Multivariate Anal.,16, 290–299 (1985).
R. Cuppens,Decomposition of Multivariate Characteristic Functions, Academic Press, New York (1975).
D. Dugué, “Sur des tests d'indépendance ‘indépendants de la loi’,”C. R. Acad. Sci. Paris Série A,281, 1103–1104 (1975).
A. Feuerverger, “A consistent test for bivariate dependence,”Int. Statist. Rev. 61, 419–433 (1993).
W. Hoeffding, “A nonparametric test for independence,”Ann. Math. Statist.,19, 546–557 (1948).
A. Kankainen,Consistent Testing of Total Independence Based on the Empirical Characteristic Function, Ph. D. Thesis, Jyväskylä Univ. Press, Jyväskylä (1995).
Author information
Authors and Affiliations
Additional information
Proceedings of the Seminar on Stability Problems for Stochastic Models, Moscow, Russia, 1996, Part I.
Rights and permissions
About this article
Cite this article
Kankainen, A., Ushakov, N.G. A consistent modification of a test for independence based on the empirical characteristic function. J Math Sci 89, 1486–1494 (1998). https://doi.org/10.1007/BF02362283
Issue Date:
DOI: https://doi.org/10.1007/BF02362283