Principal component analysis: A generalized Gini approach

A principal component analysis based on the generalized Gini correlation index is proposed (Gini PCA). The PCA generalizes standard variance. It shown, in Gaussian case, that equivalent to PCA. also proven dimensionality reduction matrix, relies city-block distances, robust outliers. Monte Carlo simulations and an application cars data (with outliers) show robustness of provide different interpretations results compared with variance