A divergence formula for regularization methods with an L2 constraint
Other Statistics
2012-03-19 v1
Abstract
We derive a divergence formula for a group of regularization methods with an L2 constraint. The formula is useful for regularization parameter selection, because it provides an unbiased estimate for the number of degrees of freedom. We begin with deriving the formula for smoothing splines and then extend it to other settings such as penalized splines, ridge regression, and functional linear regression.
Cite
@article{arxiv.1203.3559,
title = {A divergence formula for regularization methods with an L2 constraint},
author = {Yixin Fang and Yuanjia Wang and Xin Huang},
journal= {arXiv preprint arXiv:1203.3559},
year = {2012}
}