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On discrimination procedure with mixtures of continuous and categorical variables

Author

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  • Gafar Matanmi Oyeyemi
  • George Chinanu Mbaeyi
  • Saheed Ishola Salawu
  • Bernard Olagboyega Muse

Abstract

A discrimination procedure, based on the location model is described and suggested for use in situation where the discriminating variables are mixtures of continuous and binary variables. Some procedures that have been previously employed, in a similar situation, like Fisher's linear discriminant function and the logistic regression were compared with this method using error rate (ER). Optimal ERs for these procedures are reported using real and simulated data for the case of varying sample size and number of continuous and binary variables and were used as a measure for assessing the performance of the various procedures. The suggested procedure performed considerably better in the cases considered and never did produce a result that is poor when compared with other procedures. Hence, the suggested procedure might be considered for such situations.

Suggested Citation

  • Gafar Matanmi Oyeyemi & George Chinanu Mbaeyi & Saheed Ishola Salawu & Bernard Olagboyega Muse, 2016. "On discrimination procedure with mixtures of continuous and categorical variables," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(10), pages 1864-1873, August.
    • Handle: RePEc:taf:japsta:v:43:y:2016:i:10:p:1864-1873
    DOI: 10.1080/02664763.2015.1125859
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    References listed on IDEAS

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    1. Asparoukhov, Ognian K. & Krzanowski, Wojtek J., 2001. "A comparison of discriminant procedures for binary variables," Computational Statistics & Data Analysis, Elsevier, vol. 38(2), pages 139-160, December.
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