Universal Adaptive Estimations and Confidence Intervals in the Nonparametric Statistics
Abstract
The paper considers so-called adaptive estimations of regression, distribution density and spectral density of a Gaussian stationary sequence, asymptotically optimal in order at a growing number of observation on any regular subspace compactly embedded in space L2, and confidence intervals, also adaptive, are constructed on their basis for the estimated functions in an integral norm.
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