Computer Science – Information Theory
Scientific paper
2010-11-09
Computer Science
Information Theory
Scientific paper
This paper analyzes the performances of the Spearman's rho (SR) and Kendall's tau (KT) with respect to samples drawn from bivariate normal and bivariate contaminated normal populations. The exact analytical formulae of the variance of SR and the covariance between SR and KT are obtained based on the Childs's reduction formula for the quadrivariate normal positive orthant probabilities. Close form expressions with respect to the expectations of SR and KT are established under the bivariate contaminated normal models. The bias, mean square error (MSE) and asymptotic relative efficiency (ARE) of the three estimators based on SR and KT to the Pearson's product moment correlation coefficient (PPMCC) are investigated in both the normal and contaminated normal models. Theoretical and simulation results suggest that, contrary to the opinion of equivalence between SR and KT in some literature, the behaviors of SR and KT are strikingly different in the aspects of bias effect, variance, mean square error, and asymptotic relative efficiency. The new findings revealed in this work provide not only deeper insights into the two most widely used rank based correlation coefficients, but also a guidance for choosing which one to use under the circumstances where the PPMCC fails to apply.
Hou Yunhe
Hung Y. S.
Xu Weichao
Zou Yuexian
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