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An effective selection of regression variables when the error distribution is incorrectly specified

  • Wolfgang Härdle
Article

Summary

An asymptotically efficient selection of regression variables is considered in the situation where the statistician estimates regression parameters by the maximum likelihood method but fails to choose a likelihood function matching the true error distribution. The proposed procedure is useful when a robust regression technique is applied but the data in fact do not require that treatment. Examples and a Monte Carlo study are presented and relationships to other selectors such as Mallows'Cp are investigated.

Key words and phrases

Variable selection regression analysis robust regression model choice 

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Copyright information

© The Institute of Statistical Mathematics, Tokyo 1987

Authors and Affiliations

  • Wolfgang Härdle
    • 1
    • 2
  1. 1.Johann-Wolfgang-Goethe-UniversitätWest Germany
  2. 2.University of North CarolinaUSA

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