Universal Adaptive Estimations and Confidence Intervals in the Nonparametric Statistics
Probability
2007-05-23 v1 Functional Analysis
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 , and confidence intervals, also adaptive, are constructed on their basis for the estimated functions in an integral norm.
Cite
@article{arxiv.math/0406535,
title = {Universal Adaptive Estimations and Confidence Intervals in the Nonparametric Statistics},
author = {Eugene Ostrovsky and Leonid Sirota},
journal= {arXiv preprint arXiv:math/0406535},
year = {2007}
}