Journal Article

Development of Statistical Discriminant Mathematical Programming Model Via Resampling Estimation Techniques

Houshmand A. Ziari, David J. Leatham and Paul N. Ellinger

in American Journal of Agricultural Economics

Published on behalf of Agricultural and Applied Economics Association

Volume 79, issue 4, pages 1352-1362
Published in print November 1997 | ISSN: 0002-9092
Published online November 1997 | e-ISSN: 1467-8276 | DOI: http://dx.doi.org/10.2307/1244291
Development of Statistical Discriminant Mathematical Programming Model Via Resampling Estimation Techniques

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  • Mathematical Methods; Programming Methods; Mathematical and Simulation Modelling
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This paper uses resampling estimation techniques to develop a statistical mathematical programming model for discriminant analysis problems. Deleted-d jackknife, deleted-d bootstrap, and bootstrap procedures are used to identify statistical significant parameter estimates for a discriminant mathematical programming (MP) model. The results of this paper indicate that the resampling approach is a viable model selection technique. Furthermore, estimating the MP models via resampling techniques can also improve the classification performance compared to a deterministic discriminant MP model. In this study, the deleted-d jackknife procedure was the most promising among the resampling estimation techniques examined.

Keywords: credit scoring; logit; model selection; resampling; statistical mathematical program; C510; C610

Journal Article.  0 words. 

Subjects: Mathematical Methods; Programming Methods; Mathematical and Simulation Modelling ; Econometric Modelling

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