Nonparametric tests of independence using copula-based Rényi and Tsallis divergence measures.

Autor: Mohammadi, Morteza, Emadi, Mahdi
Předmět:
Zdroj: Statistics, Optimization & Information Computing; Sep2023, Vol. 11 Issue 4, p949-962, 14p
Abstrakt: We introduce new nonparametric independence tests based on R'enyi and Tsallis divergence measures and copula density function. These tests reduce the complexity of calculations because they only depend on the copula density. The copula density estimated using the local likelihood probit-transformation method is appropriate for the identification of independence. Also, we present the consistency of the copula-based R'enyi and Tsallis divergence measures estimators that are considered as test statistics. A simulation study is provided to compare the empirical power of these new tests with the independence test based on the empirical copula. The simulation results show that the suggested tests outperform in weak dependency. Finally, an application in hydrology is presented. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index