Discriminant analysis of interval data using Monte Carlo method in assessment of overlap

In this paper we show that the method of discriminant analysis (DA), on interval data by data envelopment analysis (DEA). DEA-discriminant analysis (DEA-DA) is designed to identify the existence or non-existence of an overlap between two groups, by separating hyperplane. In addition it predicts a new observation to the group which it belongs to. Data envelopment analysis technique which is developed based on the mathematical programming, evaluates the relative efficiency of a set of homogeneous decision making units. However, there are similarities between DEA and DA. DA is a method for separating two sets with previous knowledge meanwhile DEA is a technique for separating two sets efficient and inefficient without previous knowledge. Also goal programming method can be used for both of these methods.