Development of Statistical Discriminant Mathematical Programming Model Via Resampling Estimation Techniques

Houshmand A. Ziari, David Leatham () and Paul N. Ellinger

American Journal of Agricultural Economics, 1997, vol. 79, issue 4, 1352-1362

Abstract: 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. Copyright 1997, Oxford University Press.

Date: 1997
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Persistent link: https://EconPapers.repec.org/RePEc:oup:ajagec:v:79:y:1997:i:4:p:1352-1362

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