Sign-constrained least squares estimation for high-dimensional regression
Many regularization schemes for high-dimensional regression have been put forward. Most require the choice of a tuning parameter, using model selection criteria or cross-validation schemes. We show that a simple non-negative or sign-constrained least squares is a very simple and effective regulariza...
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| Format: | Journal article |
| Language: | English |
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2012
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