Quadratic location discriminant functions for mixed categorical and continuous data

W. J. Krzanowski

Statistics & Probability Letters, 1994, vol. 19, issue 2, 91-95

Abstract: The assumption of common within-cell dispersion matrices in the location model for mixtures of categorical and continuous variables is relaxed, to allow different matrices in the two populations being discriminated. This extension changes the Bayes location rule from a choice among linear functions to a choice among quadratic functions, but most of the previous methodology can be used directly in the extended case. One extra algebraic identity is provided to assist in the leave-one-out estimation of error rates for assessment of the rule, and the benefit of the extension is illustrated on a medical data set.

Keywords: Classification; rule; discriminant; function; leave-one-out; error; rates; location; model; mixed; variables (search for similar items in EconPapers)
Date: 1994
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Citations: View citations in EconPapers (2)

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