Confidence bands in density estimation

Given a sample from some unknown continuous density f.:...., we construct adaptive confidence bands that are honest for all densities in a .generic. subset of the union of t-Hölder balls, 0<t.r, where r is a fixed but arbitrary integer. The exceptional (.nongeneric.) set of densities for which our results do not hold is shown to be nowhere dense in the relevant Hölder-norm topologies. In the course of the proofs we also obtain limit theorems for maxima of linear wavelet and kernel density estimators, which are of independent interest.