van der Laan and Dudoit (2003) provide a road map for estimation and performance assessment where a parameter of … interest is defined as the risk minimizer for a suitable loss function and candidate estimators are generated using a loss … minimizing, over subsets of variables (e.g., basis functions), the empirical risk of subset-specific estimators of the parameter …

methodology, which provides a road map for estimation and performance assessment. Given a parameter of interest which can be …-validation for estimator selection and minimizing over subsets of basis functions the empirical risk of the subset-specific estimator …/substitution/addition algorithm for minimizing over subsets of variables (e.g., basis functions) the empirical risk of subset-specific estimators of …

separately in the statistical literature, including multivariate outcome prediction and density estimation based on either …Current statistical inference problems in genomic data analysis involve parameter estimation for high …, selection, and performance assessment with cross-validation. In this approach, the parameter of interest is defined as the risk …

negative log-density loss function in density estimation. Minimizing the empirical risk (i.e., the empirical mean of the loss …-validated epsilon-net estimation methodology that covers a broad class of estimation problems, including multivariate outcome prediction … interest (i.e., the risk minimizer for the true data generating distribution). In this article, we propose a cross …

An important problem in epidemiology and medical research is the estimation of a causal effect of a treatment action at … adaptive loss-based estimation (as in machine learning) methodology, involving cross-validation to data adaptively select model … addition, we provide an application involving the estimation of the effect of lung function on survival in an elderly …