A Note on the Ordinal Canonical Correlation Analysis of Two Sets of Ranking Scores

21 Pages Posted: 15 Jan 2009

Date Written: January 15, 2009

Abstract

In this paper we have proposed a method to conduct the ordinal canonical correlation analysis (OCCA) that yields ordinal canonical variates and the coefficient of correlation between them, which is analogous to the rank correlation coefficient of Spearman. The ordinal canonical variates are themselves analogous to the canonical variates obtained by the conventional canonical correlation analysis (CCCA). Our proposed method is suitable to deal with the multivariable ordinal data arrays. Our examples have shown that in finding canonical rank scores and canonical correlation from an ordinal dataset, the CCCA is suboptimal. The OCCA suggested by us outperforms the conventional method. Moreover, our method can take care of any of the five different schemes of rank ordering. It uses the Particle Swarm Optimizer which is one of the recent and prized meta-heuristics for global optimization. The computer program developed by us is fast and accurate. It has worked very well to conduct the OCCA.

Suggested Citation

Mishra, Sudhanshu K., A Note on the Ordinal Canonical Correlation Analysis of Two Sets of Ranking Scores (January 15, 2009). Available at SSRN: https://ssrn.com/abstract=1328319 or http://dx.doi.org/10.2139/ssrn.1328319

Sudhanshu K. Mishra (Contact Author)

North-Eastern Hill University (NEHU) ( email )

NEHU Campus
Shillong, 793022
India
03642550102 (Phone)

HOME PAGE: http://www.nehu-economics.info

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