On adaptive nonparametric inference
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If you have a question about this talk, please contact Richard Nickl.
One of the intriguing problems in the paradigm of adaptive
nonparametric function estimation as developed in the last two decades by
Donoho, Johnstone, Lepski, Birge, Massart, Kerkyacharian, Picard, Tsybakov,
Spokoiny, Cai, Low and many others, is what one could call the ‘hiatus’
between estimation and inference, or, to be more precise, between the
existence of adaptive risk bounds and the non-existence of adaptive
confidence statements. Considering the fundamental problem of the existence
of adaptive confidence bands, we show that this fact is deeply connected to
certain nonparametric hypothesis testing problems studied by the Russian
school (Ingster and others), and we use this connection to derive necessary
and sufficient conditions for the existence of adaptive confidence
statements, thus characterising the exact boundaries of when adaptive
inference is possible and when not.
This talk is part of the Statistics series.
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