Large datasets are increasingly widespread in many disciplines. The exponential growth of data requires the development more analysis methods order to process information efficiently. In better visualize data, such as Principal Component Analysis (PCA) and MultiDimensional Scaling (MDS) allow extract a low-dimensional structure from high-dimensional set. proposed approach, called Topological (T...

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 interp...