Abstract
Research on modelprocedure selection has focused on selecting a single model globally. In many applications, especially for high-dimensional or complex data, however, the relative performance of the candidate procedures typically depends on the location, and the globally best procedure can often be improved when selection of a model is allowed to depend on location. We consider localized model selection methods and derive their theoretical properties.
Original language | English (US) |
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Pages (from-to) | 472-492 |
Number of pages | 21 |
Journal | Econometric Theory |
Volume | 24 |
Issue number | 2 |
DOIs | |
State | Published - Apr 2008 |