Model search by bootstrap "bumping"

We propose a bootstrap-based method for enhancing a search through a space of models. The technique is well suited to complex, adaptively fitted model s-it provides a convenient method for finding better local minima and for r esistant fitting. Applications to regression, classification, and density e stimation are described. We also provide results on the asymptotic behavior of bumping estimates.