作者：Bull, Adam D.; Nickl, Richard
作者单位：University of Cambridge
摘要：The problem of constructing confidence sets that are adaptive in -loss over a continuous scale of Sobolev classes of probability densities is considered. Adaptation holds, where possible, with respect to both the radius of the Sobolev ball and its smoothness degree, and over maximal parameter spaces for which adaptation is possible. Two key regimes of parameter constellations are identified: one where full adaptation is possible, and one where adaptation requires critical regions be removed. T...
