Model selection in equations with many 'small' effects
High dimensional general unrestricted models (GUMs) may include important individ-ual determinants, many small relevant effects, and irrelevant variables. Automatic modelselection procedures can handle more candidate variables than observations, allowing substantial dimension reduction from GUMs wit...
| 主要な著者: | , , |
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| フォーマット: | Journal article |
| 出版事項: |
Wiley
2013
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