The rowwise correlation between two proximity matrices and the partial rowwise correlation
- Han de Vries
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This paper discusses rowwise matrix correlation, based on the weighted sum of correlations between all pairs of corresponding rows of two proximity matrices, which may both be square (symmetric or asymmetric) or rectangular. Using the correlation coefficients usually associated with Pearson, Spearman, and Kendall, three different rowwise test statistics and their normalized coefficients are discussed, and subsequently compared with their nonrowwise alternatives like Mantel'sZ. It is shown that the rowwise matrix correlation coefficient between two matricesX andY is the partial correlation between the entries ofX andY controlled for the nominal variable that has the row objects as categories. Given this fact, partial rowwise correlations (as well as multiple regression extensions in the case of Pearson's approach) can be easily developed.
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- The rowwise correlation between two proximity matrices and the partial rowwise correlation
Volume 58, Issue 1 , pp 53-69
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- matrix permutation tests
- rowwise matrix correlation
- partial matrix correlation
- Mantel'sZ statistic
- nonparametric statistics
- Industry Sectors
- Han de Vries (1)
- Author Affiliations
- 1. Projectgroup of Ethology & Socio-ecology, The University of Utrecht, Postbox 80.086, 3508 TB, Utrecht, The Netherlands