With Stéphane Mussard and Téa Ouraga, we recently uploaded on arxiv a paper Principal Component Analysis: A Generalized Gini Approach,
A principal component analysis based on the generalized Gini correlation index is provided. It is proven that the reduction dimensionality based on the generalized Gini correlation index, that relies on city-block distances, is robust to outliers.
Some codes are also available on a dedicated github repo.
Cite this blog post
Arthur Charpentier (2019, October 23). Principal Component Analysis: A Generalized Gini Approach. Freakonometrics. Retrieved March 19, 2024, from https://doi.org/10.58079/ove1
Thanks for sharing