On the Asymptotic Distribution of the Location Linear Discriminant Function
Ioannis G. Vlachonikolis · Journal of the Royal Statistical Society Series B (Statistical Methodology) · 1985
SUMMARY The location linear discriminant function forms the basis of the optimal Bayes classification rule when the data contain both binary and continuous variables (Krzanowski, 1975). When the unknown parameters are replaced by their sample estimates, the resulting “estimative” rule has an exact distribution which is too complicated for numerical use. We present here an asymptotic expansion of this distribution and study its performance under various assumptions about the parameters.