Digitale Medien
Oxford, UK
:
Blackwell Publishing Ltd
Decision sciences
19 (1988), S. 0
ISSN:
1540-5915
Quelle:
Blackwell Publishing Journal Backfiles 1879-2005
Thema:
Wirtschaftswissenschaften
Notizen:
There are numerous variable selection rules in classical discriminant analysis. These rules enable a researcher to distinguish significant variables from nonsignificant ones and thus provide a parsimonious classification model based solely on significant variables. Prominent among such rules are the forward and backward stepwise variable selection criteria employed in statistical software packages such as Statistical Package for the Social Sciences and BMDP Statistical Software. No such criterion currently exists for linear programming (LP) approaches to discriminant analysis. In this paper, a criterion is developed to distinguish significant from nonsignificant variables for use in LP models. This criterion is based on the “jackknife” methodology. Examples are presented to illustrate implementation of the proposed criterion.
Materialart:
Digitale Medien
URL:
http://dx.doi.org/10.1111/j.1540-5915.1988.tb00286.x
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