Testing Kendall's τ for a large class of dependent sequences. Issue 4 (3rd July 2020)

• Record Type: Journal Article
• Authors: Ammous, Sinda
• Is Part Of: Statistics. Volume 54:Issue 4(2020)
• Page Start: 686
• Page End: 713
• Publication Date: 2020-07-03
• Subjects: U-statistics -- Kendall's tau -- hypothesis testing -- bivariate dependent sequences -- β-mixing sequences -- Markov chains; 62G10 -- 62G20 -- 62M10; Mathematical statistics -- Periodicals; 519.505
• DOI: 10.1080/02331888.2020.1775596
• Languages: English
• ISSNs: 0233-1888

Abstract

ABSTRACT: Let ( X i, Y i ) i ∈ Z be a stationary sequence of R 2 -valued random variables. To test if X 1 and Y 1 are correlated in the sense of Kendall, we propose a robust correction of the usual Kendall test, valid for a large class of dependent sequences. We also show that the condition on the dependency coefficients is quasi-optimal in a certain sense, and we illustrate our results trough different sets of simulation.