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Journal of Applied Mathematics
Volume 2012, Article ID 315868, 14 pages
Research Article

An Application of Monte-Carlo-Based Sensitivity Analysis on the Overlap in Discriminant Analysis

Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran

Received 22 June 2012; Revised 21 September 2012; Accepted 25 September 2012

Academic Editor: George Jaiani

Copyright © 2012 S. Razmyan and F. Hosseinzadeh Lotfi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Discriminant analysis (DA) is used for the measurement of estimates of a discriminant function by minimizing their group misclassifications to predict group membership of newly sampled data. A major source of misclassification in DA is due to the overlapping of groups. The uncertainty in the input variables and model parameters needs to be properly characterized in decision making. This study combines DEA-DA with a sensitivity analysis approach to an assessment of the influence of banks’ variables on the overall variance in overlap in a DA in order to determine which variables are most significant. A Monte-Carlo-based sensitivity analysis is considered for computing the set of first-order sensitivity indices of the variables to estimate the contribution of each uncertain variable. The results show that the uncertainties in the loans granted and different deposit variables are more significant than uncertainties in other banks’ variables in decision making.