A new Gini correlation between quantitative and qualitative variables

2018/09/26 by Xin Dang, Dao Nguyen, Dang, Xin +5 · 1 citation
Mathematics · Economics, Econometrics and Finance · #Advanced Statistical Methods and Models #Complex Systems and Time Series Analysis #Statistical Methods and Inference

paper · pdf · doi:10.48550/arxiv.1809.09793

Abstract

We propose a new Gini correlation to measure dependence between a categorical and numerical variables. Analogous to Pearson R² in ANOVA model, the Gini correlation is interpreted as the ratio of the between-group variation and the total variation, but it characterizes independence (zero Gini correlation mutually implies independence). Closely related to the distance correlation, the Gini correlation is of simple formulation by considering the nature of categorical variable. As a result, the proposed Gini correlation has a lower computational cost than the distance correlation and is more straightforward to perform inference. Simulation and real applications are conducted to demonstrate the advantages.

Citations

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Cited by

• Quantifying and testing dependence to categorical variables

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