function representations computed on each bootstrap sample, thereby reducing computational time considerably. This method is … improvement in the numerical speed of the fast bootstrap method. …

We characterize the robustness of subsampling procedures by deriving a formula for the breakdown point of subsampling … quantiles. This breakdown point can be very low for moderate subsampling block sizes, which implies the fragility of subsampling … can be applied instead. To overcome these robustness problems, we introduce a consistent robust subsampling procedure for …

—both the subsampling method and a plug-in approach. Simulation studies compare the size and power of both approaches as applied … to hypothesis testing for the mean. Both methods perform well–although the subsampling method appears to be better sized …

principle components and other shrinkage techniques, including Bayesian model averaging and various bagging, boosting, least …

discontinuous and must be regularized to permit consistent estimation. The optimal regularization parameter depends on population … regularization parameter in series estimation. The method adapts to the unknown smoothness of g and other unknown functions. The …