General regularization schemes for signal detection in inverse problems
Statistics Theory
2013-04-04 v1 Statistics Theory
Abstract
The authors discuss how general regularization schemes, in particular linear regularization schemes and projection schemes, can be used to design tests for signal detection in statistical inverse problems. It is shown that such tests can attain the minimax separation rates when the regularization parameter is chosen appropriately. It is also shown how to modify these tests in order to obtain (up to a factor) a test which adapts to the unknown smoothness in the alternative. Moreover, the authors discuss how the so-called \emph{direct} and \emph{indirect} tests are related via interpolation properties.
Cite
@article{arxiv.1304.0943,
title = {General regularization schemes for signal detection in inverse problems},
author = {Clément Marteau and Peter Mathé},
journal= {arXiv preprint arXiv:1304.0943},
year = {2013}
}