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Computerized Construction in Fortran of a Discriminant Function for Categorical Data

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  • Elizabeth Sturt

Abstract

A non‐parametric discriminant function for categorical or discrete‐valued data belonging to at least two a priori classes is constructed by a computer program from the base sample data. There is no limit to the number of data variables measured oh members of the base sample, but each variable can have no more than 10 possible values. The program prints out the discriminant function in the form of a branching key for use by hand; also in the form of a Fortran function which can be punched out on cards by the computer. A simple program to read the same variables for each individual, and then call the function, will classify a prospective series from the same population. The key itself may have a descriptive use, especially when the number of variables is enormous. In this case it may be used as a preliminary analysis which may suggest testable hypotheses about the interactions between some of the variables. The algorithm itself is presented in the algorithms section of this issue of Applied Statistics (Sturt, 1980).

Suggested Citation

  • Elizabeth Sturt, 1981. "Computerized Construction in Fortran of a Discriminant Function for Categorical Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 30(3), pages 213-222, November.
    • Handle: RePEc:bla:jorssc:v:30:y:1981:i:3:p:213-222
    DOI: 10.2307/2346344
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