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Generalized Information Criteria for the Best Logit Model

  • Christos P. KitsosEmail author
  • Thomas L. Toulias
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 136)

Abstract

In this paper the \(\gamma \)–order Generalized Fisher’s entropy type Information measure (\(\gamma \)–GFI) is adopted as a criterion for the selection of the best Logit model. Thus the appropriate Relative Risk model can be evaluated through an algorithm. The case of the entropy power is also discussed as such a criterion. Analysis of a real breast cancer data set is conducted to demonstrate the proposed algorithm, while algorithm’s realizations, through MATLAB scripts, are cited in Appendix.

Keywords

Fisher’s entropy measure Logit model Relative Risk Breast Cancer 

Notes

Acknowledgments

The authors would like to thank the referees who improved the language as well as the content of this paper, with their valuable comments.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Technological Educational Institute of AthensEgaleo, AthensGreece

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