Small Sample Results for a Discriminant Function Estimated from a Mixture of Two Inverse Gaussian Distributions

Abstract

Estimation of a discriminant function on the basis of a small sample size from a mixture of two inverse Gaussian distributions is considered. Its performance is investigated by a series of simulation experiments. The relative efficiency of the mixture and classified discrimination procedures are evaluated from the simulation results and compared with available asymptotic relative efficiency results.