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 v...

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Main Authors: S. Razmyan, F. Hosseinzadeh Lotfi
Format: Article
Language:English
Published: Wiley 2012-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2012/315868
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author S. Razmyan
F. Hosseinzadeh Lotfi
author_facet S. Razmyan
F. Hosseinzadeh Lotfi
author_sort S. Razmyan
collection DOAJ
description 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.
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spelling doaj-art-92c1ec19584446cb8c7849a00ebaf69f2025-02-03T06:00:28ZengWileyJournal of Applied Mathematics1110-757X1687-00422012-01-01201210.1155/2012/315868315868An Application of Monte-Carlo-Based Sensitivity Analysis on the Overlap in Discriminant AnalysisS. Razmyan0F. Hosseinzadeh Lotfi1Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, IranDepartment of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, IranDiscriminant 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.http://dx.doi.org/10.1155/2012/315868
spellingShingle S. Razmyan
F. Hosseinzadeh Lotfi
An Application of Monte-Carlo-Based Sensitivity Analysis on the Overlap in Discriminant Analysis
Journal of Applied Mathematics
title An Application of Monte-Carlo-Based Sensitivity Analysis on the Overlap in Discriminant Analysis
title_full An Application of Monte-Carlo-Based Sensitivity Analysis on the Overlap in Discriminant Analysis
title_fullStr An Application of Monte-Carlo-Based Sensitivity Analysis on the Overlap in Discriminant Analysis
title_full_unstemmed An Application of Monte-Carlo-Based Sensitivity Analysis on the Overlap in Discriminant Analysis
title_short An Application of Monte-Carlo-Based Sensitivity Analysis on the Overlap in Discriminant Analysis
title_sort application of monte carlo based sensitivity analysis on the overlap in discriminant analysis
url http://dx.doi.org/10.1155/2012/315868
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