Nonnegative Garrote Component Selection in Functional ANOVA models
Published 11 March 2007
Ming Yuan
Citations34
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TL;DR
It is shown that the whole solution path of the proposed nonparametric extension of the nonnegative garrote can be efficiently computed, which facilitates the selection of the tuning parameter.
Abstract
We consider the problem of component selection in a functional ANOVA model. A nonparametric extension of the nonnegative garrote (Breiman, 1996) is proposed. We show that the whole solution path of the proposed method can be efficiently computed, which, in turn, facilitates the selection of the tuning parameter. We also show that the final estimate enjoys nice theoretical properties given that the tuning parameter is appropriately chosen. Simulation and a real data example demonstrate promising performance of the new approach.
Keywords
Mathematics
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