off estimation and approximation errors by minimizing the sum of an empirical risk term and a complexity penalty. It is …, however, where complexity penalties like this give loose upper bounds on the estimation error. In particular, if we choose a … function from a suitably simple convex function class with a strictly convex loss function, then the estimation error (the …

standard and international trade. The estimation results allow us to formulate some interesting policy conclusions. …

We consider the problem of model assessment by risk estimation. Variousapproaches to risk estimation are considered in … proposed byDavid Haussler. Point and interval estimation based on test samples andtraining samples is discussed, with interval …

In terms of risk measurement, probability and quantile risk estimation have developed enormously in the past decade … illustrates the estimation bias that exists when assuming normality is minimized for the conditional EVT approach, both for single …