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- W169210055 abstract "At the basis of combinatorial methods in density estimation introduced by Devroye and Lugosi is the so-called Sche¤e selection rule. We show by an examples that this rule based on L1 errors may not bring the selection closer to optimality than tossing of a coin. As in any estimation problem, the choice of a criterion is at the heart of the matter. The optimality of the Sche¤e estimate is perceived di¤erently by di¤erent divergence criteria. We show that the L1 oracle inequality satis ed by the Sche¤e estimate can be extended to divergences. It can be also extended to estimates associated with selection rules based on divergences. As the L1 rule, the new rules are applicable to any selection problem in density estimation. AMS 1991 subject classi cation: 62G05." @default.
- W169210055 created "2016-06-24" @default.
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- W169210055 date "2008-01-01" @default.
- W169210055 modified "2023-09-27" @default.
- W169210055 title "Divergence criteria for improved selection rules" @default.
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