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A note on the comparison of logit and discriminant models of consumer credit behaviourby: J. C. Wiginton
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AbstractSince the early work of D. Durand, there has been considerable interest in using quantitative models of consumer credit behavior for credit-granting decisions. Most models are based on the concept of "scoring" by use of weights usually determined as statistically significant coefficients of some linear statistical model, frequently the linear discriminant model. The main drawback to the linear discriminant model is that it implicitly assumes that the attribute measurements arise from multivariate normal populations such that the classes have identical covariarice matrices, differing only in the value of their mean vectors. In the present context, it is unlikely that the covariance matrices are equal.
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