On the Optimality of Prediction-based Selection Criteria and the Convergence Rates of Estimators
基于预测的选择准则之最优性与估计量收敛速度
Summary Several estimators of squared prediction error have been suggested for use in model and bandwidth selection problems. Among these are cross-validation, generalized cross-validation and a number of related techniques based on the residual sum of squares. For many situations with squared error loss, e.g. nonparametric smoothing, these estimators have been shown to be asymptotically optimal in the sense that in large samples the estimator minimizing the selection…