Model Search by Bootstrap “Bumping”
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TL;DR
A bootstrap-based method for enhancing a search through a space of models is proposed, well suited to complex, adaptively fitted models and provides a convenient method for finding better local minima and for resistant fitting.
Abstract
Abstract We propose a bootstrap-based method for enhancing a search through a space of models. The technique is well suited to complex, adaptively fitted models—it provides a convenient method for finding better local minima and for resistant fitting. Applications to regression, classification, and density estimation are described. We also provide results on the asymptotic behavior of bumping estimates.