Journal of Applied Mathematics
- J. Appl. Math.
- Volume 2012 (2012), Article ID 315868, 14 pages.
An Application of Monte-Carlo-Based Sensitivity Analysis on the Overlap in Discriminant Analysis
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.
J. Appl. Math., Volume 2012 (2012), Article ID 315868, 14 pages.
First available in Project Euclid: 2 January 2013
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Razmyan, S.; Hosseinzadeh Lotfi, F. An Application of Monte-Carlo-Based Sensitivity Analysis on the Overlap in Discriminant Analysis. J. Appl. Math. 2012 (2012), Article ID 315868, 14 pages. doi:10.1155/2012/315868. https://projecteuclid.org/euclid.jam/1357153575