Applications of Robust Methods in Modern Data Science
Journal: Journal of Applied Statistics
Focus on robust statistical methods in modern data analysis under realistic conditions such as outliers, noise, and heterogeneity. Emphasis on both methodological developments and practical applications. Topics include robust inference in high-dimensional settings, scalable algorithms, and robust approaches for complex data structures (e.g., functional, compositional, and network data). Applications in engineering,…