Estimation of a nonlinear discriminant function from a mixture of two exponentiated - Weibull distributions

Abstract

In this paper, a procedure for finding maximum likelihood estimates (MLEs) of the parameters of a finite mixture of two exponentiated-Weibull distributions (MEW) is presented, using classified and unclassified observations. Estimation of a nonlinear discriminant function on the basis of a small sample size is considered. Its performance is investigated by a series of simulation experiments. The simulations conducted for estimating a nonlinear discriminant function by the maximum likelihood method, on the basis of unclassified data drawn from a mixture of the underlying populations suggest that the error rate can be reduced by a substantial percentage for widely separated populations. Generally, the performance of the mixture discrimination procedure relative to the completely classified procedure, measured by total probabilities is good.