Thus, we can use Kendall’s τ to derive \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\hat {\rho }_{\text {\textit {j,k}}}$\end{document}ρ^j,k as \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$\sin \left (\frac {\pi \hat {\tau }_{\text {\textit {j,k}}}}{2}\right)$\end{document}sinπτ^j,k2. In the simulation study, we evaluate the robustness of Kendall’s τ in comparison to Pearson’s sample correlation coefficient.
