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Additive models in high dimensions

Hegland, Markus; Pestov, Vladimir


Additive decompositions are established tools in nonparametric statistics and effectively address the curse of dimensionality. For the analysis of the approximation properties of additive decompositions, we introduce a novel framework which includes the number of variables as an ingredient in the definition of the smoothness of the underlying functions. This approach is motivated by the effect of concentration of measure in high dimensional spaces. Using the resulting smoothness conditions,...[Show more]

CollectionsANU Research Publications
Date published: 2005
Type: Journal article
Source: ANZIAM Journal


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