B0255
Title: Robust shrinkage-based methods
Authors: Elisa Cabana Garceran del Vall - CUNEF, SL (Spain) [presenting]
Rosa Lillo - Universidad Carlos III de Madrid (Spain)
Abstract: The aim is to summarize the key findings and results obtained from the research encompassing four distinct papers focused on developing robust methods based on the notion of shrinkage. The research addresses the challenges associated with multivariate outlier detection, robust regression, robust quality control, and robust classification, ultimately contributing to the advancement of these critical areas in data analysis. The methods demonstrate superior performance compared to existing techniques, showcasing their efficacy in diverse application domains.
