B. Ofuru

Variable Selection under Multicollinearity and Heavy-Tailed Errors: A Systematic Assessment of Classical and Penalized Methods

Variable selection in high-dimensional regression becomes particularly challenging when multicollinearity and heavy-tailed errors occur simultaneously. This study systematically evaluates the performance boundaries of classical, shrinkage, sparse, and robust regression methods under these conditions. A Monte Carlo simu...