, Volume 50, Issue 2, pp 163–172 | Cite as

The mixture index of fit and minimax regression

  • Tamás Rudas


A measure of the fit of a statistical model can be obtained by estimating the relative size of the largest fraction of the population where a distribution belonging to the model may be valid. This is the mixture index of fit that was suggested for models for contingency tables by Rudas, Clogg, Lindsay (1994) and it is extended here for models involving continuous observations. In particular, the approach is applied to regression models with normal and uniform error structures. Best fit, as measured by the mixture index of fit, is obtained with minimax estimation of the regression parameters. Therefore, whenever minimax estimation is used for these problems, the mixture index of fit provides a natural approach for measuring model fit and for variable selection.

Key words: Minimax estimation, minimum distance estimation, mixture index of fit, regression with uniform error, variable selection 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Tamás Rudas
    • 1
  1. 1.Department of Statistics, Eötvös Loránd University and TÁRKI, Pollack M. tér 10., H-1088 Budapest, Hungary (e-mail:

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