ABSTRACT
Estimators aggregation is an alternative to model selection for exploiting possible unknown structures in the data. The main idea is to use a convex combination of a collection of estimators instead of selecting one among them. Estimator aggregation shares all the good properties of model selection. Unfortunately, it suffers from the same high-computational cost. Some approximate computations can be implemented; some of them are described at the end of the chapter.
