期刊
STATISTICS & PROBABILITY LETTERS
卷 81, 期 1, 页码 62-70出版社
ELSEVIER
DOI: 10.1016/j.spl.2010.09.019
关键词
Epsilon-insensitive loss; Quantile regression; Reproducing kernel Hilbert space
资金
- Inha University
This paper proposes a method to estimate the conditional quantile function using an epsilon-insensitive loss in a reproducing kernel Hilbert space. When choosing a smoothing parameter in nonparametric frameworks, it is necessary to evaluate the complexity of the model. In this regard, we provide a simple formula for computing an effective number of parameters when implementing an epsilon-insensitive loss. We also investigate the effects of the epsilon-insensitive loss. (C) 2010 Elsevier B.V. All rights reserved.
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