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Beschreibung:
We attempt to recover a regression function from noisy data. It is assumed that the underlying function is a piecewise entire analytic function. Types and the number of singularities are assumed to be unknown. We show how to chose smoothing parameters and a wavelet basis to achieve the asymptotically minimax risk up to the constant.