Asymptotic Properties of Generalized Cross Validation Estimators for Regularized System Identification
Asymptotic Properties of Generalized Cross Validation Estimators for Regularized System Identification is a scholarly work, published in 2018 in ''IFAC Proceedings Volumes''. The main subjects of the publication include regularization, mathematics, hyperparameter, Monte Carlo method, identification, system identification, uncertainty quantification, statistics, estimator, infinity, mean squared error, applied mathematics, and cross-validation. The authors study the asymptotic properties of the generalized cross validation (GCV) hyperparameter estimator and establish its connection with the Stein's unbiased risk estimators (SURE) as well as the mean squared error (MSE).