Abstract
In this paper, we study the problem of pointwise estimation of a multivariate function. We develop a general pointwise estimation procedure that is based on selection of estimators from a large parameterized collection. An upper bound on the pointwise risk is established and it is shown that the proposed selection procedure specialized for different collections of estimators leads to minimax and adaptive minimax estimators in various settings.
Citation
Alexander Goldenshluger. Oleg Lepski. "Universal pointwise selection rule in multivariate function estimation." Bernoulli 14 (4) 1150 - 1190, November 2008. https://doi.org/10.3150/08-BEJ144
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