Localized model selection for regression

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5 Scopus citations


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 languageEnglish (US)
Pages (from-to)472-492
Number of pages21
JournalEconometric Theory
Issue number2
StatePublished - Apr 2008


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