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Discrimination with Mixed Binary and Continuous Data

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  • I. G. Vlachonikolis
  • F. H. C. Marriott

Abstract

This paper consists of a case study in the use of different methods of Discriminant analysis. Methods used include Fisher's Linear discriminant function, various modifications of this technique, Logistic discrimination and Kernel methods using jack‐knife maximum likelihood. These methods are applied on two sets of data. Their success is compared using the proportions misclassified, estimated by the “leaving‐one‐out” method where possible.

Suggested Citation

  • I. G. Vlachonikolis & F. H. C. Marriott, 1982. "Discrimination with Mixed Binary and Continuous Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 31(1), pages 23-31, March.
    • Handle: RePEc:bla:jorssc:v:31:y:1982:i:1:p:23-31
    DOI: 10.2307/2347071
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    Cited by:

    1. Leung, Chi-Ying, 1999. "Covariance Adjustments in Discrimination of Mixed Discrete and Continuous Variables," Journal of Multivariate Analysis, Elsevier, vol. 71(1), pages 111-124, October.
    2. Krzanowski, W. J., 1995. "Selection of variables, and assessment of their performance, in mixed-variable discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 19(4), pages 419-431, April.
    3. Ioannis G. Vlachonikolis & Dimitris A. Karras & Manolis J. Hatzakis & Nicholas Paritsis, 2000. "Improved Statistical Classification Methods in Computerized Psychiatric Diagnosis," Medical Decision Making, , vol. 20(1), pages 95-103, January.

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