Penalised Euclidean distance regression
A method is introduced for variable selection and prediction in linear regression problems where the number of predictors can be much larger than the number of observations. The methodology involves minimising a penalised Euclidean distance, where the penalty is the geometric mean of the $\ell_1$ an...
| Main Authors: | , , |
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| Format: | Article |
| Published: |
Wiley
2018
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| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/48710/ |