科研之友
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摘要
This paper focuses on recovering an unknown vector beta from the noisy data Y = X beta + sigma xi, where X is a known n x p-matrix, xi is a standard white Gaussian noise, and sigma is an unknown noise level. In order to estimate beta, a spectral regularization method is used, and our goal is to choose its regularization parameter with the help of the data Y. In this paper, we deal solely with regularization methods based on the so-called ordered smoothers (see [13]) and extend the oracle in equality from [11] to the case, where the noise level is unknown.
- 出版日期2011
