A Comparison of Segment Retention Criteria for Finite Mixture Logit Models

@article{Andrews2003ACO,
  title={A Comparison of Segment Retention Criteria for Finite Mixture Logit Models},
  author={R. Andrews and Imran S. Currim},
  journal={Journal of Marketing Research},
  year={2003},
  volume={40},
  pages={235 - 243}
}
  • R. Andrews, Imran S. Currim
  • Published 2003
  • Mathematics
  • Journal of Marketing Research
  • Despite the widespread application of finite mixture models in marketing research, the decision of how many segments to retain in the models is an important unresolved issue. Almost all applications of the models in marketing rely on segment retention criteria such as Akaike's information criterion, Bayesian information criterion, consistent Akaike's information criterion, and information complexity to determine the number of latent segments to retain. Because these applications employ real… CONTINUE READING
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    References

    SHOWING 1-10 OF 46 REFERENCES