3 papers
q-fin.ST2025
Holdout cross-validation for large non-Gaussian covariance matrix estimation using Weingarten calculus
Lamia Lamrani, Benoît Collins, Jean-Philippe Bouchaud
Cross-validation is one of the most widely used methods for model selection and evaluation; its efficiency for large covariance matrix estimation appears robust in practice, but li…
math.ST2025
Optimal Data Splitting for Holdout Cross-Validation in Large Covariance Matrix Estimation
Lamia Lamrani, Christian Bongiorno, Marc Potters
Cross-validation is a statistical tool that can be used to improve large covariance matrix estimation. Although its efficiency is observed in practical applications and a convergen…
stat.CO2024
Quantifying the information lost in optimal covariance matrix cleaning
Christian Bongiorno, Lamia Lamrani
Obtaining an accurate estimate of the underlying covariance matrix from finite sample size data is challenging due to sample size noise. In recent years, sophisticated covariance-c…