Model selection in equations with many 'small' effects

Model selection in equations with many 'small' effects

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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...

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Библиографические подробности
Главные авторы:	Castle, J, Doornik, J, Hendry, D
Формат:	Journal article
Опубликовано:	Wiley 2013

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