estimators in the prediction of a univariate outcome by minimizing an empirical risk, and it uses cross-validation to select fine …

the performance of the resulting estimator. We propose a unified loss-based methodology for estimator construction … separately in the statistical literature, including multivariate outcome prediction and density estimation based on either … uncensored or censored data. This article provides an overview of the methodology and describes its application to two problems …

-validated epsilon-net estimation methodology that covers a broad class of estimation problems, including multivariate outcome prediction … generalizations of the proposed estimation methodology to censored data structures. …

methodology, which provides a road map for estimation and performance assessment. Given a parameter of interest which can be … with a new class of loss-based cross-validated algorithms in prediction of univariate and multivariate outcomes …