Distance Correlation Measures Applied to
Analyze Relation between Variables in Liver
Cirrhosis Marker Data

Santam Chakraborty; Atanu Bhattacharjee

Abstract

Distance Correlation Measures Applied to Analyze Relation between Variables in Liver Cirrhosis Marker Data

Distance correlation (DC) is a new choice to compute the relation between variables. However, the Bayesian counterpart of Distance Correlation is not well established. In this paper, a Bayesian counterpart of Distance Correlation is proposed. The proposed method is illustrated with Liver Cirrhosis Marker data. Previously published data on the relation between aspartate transaminase (AST) and alanine transaminase (ALT) is used to formulate the prior information for Bayesian computation. The computed DC using the proposed method between AST and ALT (both of which are markers of liver function) is 0.44. The credible interval is ranges 0.41 to 0.46. Bayesian counterpart proposed herein to compute DC coefficient is simple and handy.