  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.
