On Testing Significance of the Multivariate Rank Correlation Coefficient

Authors

  • Grzegorz Kończak University of Economics in Katowice, Faculty of Management, Department of Statistics, Econometrics and Mathematics

DOI:

https://doi.org/10.18778/0208-6018.335.02

Keywords:

multivariate Spearman’s rho, copula function, permutation tests, Monte Carlo study

Abstract

The Spearman’s rho is a measure of the strength of the association between two variables. There are some extensions of this coefficient for the multivariate case. Measures of the multivariate association which are the generalisation of the bivariate Spearman’s rho are considered in the literature. These measures are based on copula functions. This article presents a proposal of the testing for the multivariate Spearman’s rank correlation coefficient. The proposed test is based on the permutation method. The test statistic used in the permutation test is based on the empirical copula function. The properties of the proposed method have been described using computer simulations.

 

Downloads

Download data is not yet available.

References

Bedő J., Ong Ch.S. (2015), Multivariate Spearman’s rho for rank aggregation, arxiv.org [accessed: 12.12.2016].
Google Scholar

Berry K.J., Johnston J.E., Mielke Jr. P.W. (2014), A Chronicle of Permutation Statistical Methods, Springer International Publishing, New York.
Google Scholar

Domański Cz., Pruska K. (2000), Nieklasyczne metody statystyczne, Polskie Wydawnictwo Ekonomiczne, Warszawa.
Google Scholar

Efron B., Tibshirani R. (1993), An Introduction to the Bootstrap, Chapman & Hall, New York.
Google Scholar

Good P. (2005), Permutation, Parametric and Bootstrap Tests of Hypotheses, Science Business Media Inc., New York.
Google Scholar

Joe H. (1990), Multivariate Concordance, “Journal of Multivariate Analysis”, no. 35, pp. 12–30.
Google Scholar

Kończak G. (2016), Testy permutacyjne. Teoria i zastosowania, Uniwersytet Ekonomiczny w Katowicach, Katowice.
Google Scholar

Lehmann E.L. (2009), Parametric vs. nonparametric: Two alternative methodologies, “Journal of Nonparametric Statistics”, no. 21 pp. 397–405.
Google Scholar

Nelsen R.B. (1996), Nonparametric Measures of Multivariate Association, “IMS Lecture Notes – Monograph Series”, no. 28, pp. 223–232.
Google Scholar

Nelsen R.B. (1999), An Introduction to Copulas, Springer Verlag, New York.
Google Scholar

Schmid F., Schmidt R. (2006), Bootstraping Spearman’s Multivariate Rho, Proceedings of COMPSTAT 2006, pp. 759–766.
Google Scholar

Schmid F., Schmidt R. (2007), Multivariate Extensions of Spearman’s Rho and Related Statistics, “Statistics & Probability Letters”, no. 77, pp. 407–416.
Google Scholar

Sheskin D.J. (2004), Handbook of Parametric and Nonparametric Statistical Procedures, Chapman & Hall/CRC, Boca Raton.
Google Scholar

Wywiał J. (2004), Wprowadzenie do wnioskowania statystycznego, Akademia Ekonomiczna w Katowicach, Katowice.
Google Scholar

Zar J.H. (1972), Significance Testing of the Spearman Rank Correlation Coefficient, “Journal of the American Statistical Association”, vol. 67, no. 339, pp. 578–580.
Google Scholar

Zar J.H. (2010), Biostatistical Analysis, Pearson Prentice Hall, New Jersey.
Google Scholar

Downloads

Published

2018-05-16

How to Cite

Kończak, G. (2018). On Testing Significance of the Multivariate Rank Correlation Coefficient. Acta Universitatis Lodziensis. Folia Oeconomica, 3(335), 21–34. https://doi.org/10.18778/0208-6018.335.02

Issue

Section

Articles

Similar Articles

<< < 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 > >> 

You may also start an advanced similarity search for this article.