… involving qualitative variables in logistic regression. We contrast the merits of logistic
regression maximum likelihood estimators (MLEs) with those of discriminant function estimators. …

… correctly, which turns out to be the case for the logistic regression and normal discriminant
… 8 for the logistic regression procedure and the normal discriminant procedure and then use …

… The goal of this paper was to compare logistic regression and linear discriminant
analysis in order to set some guidelines to make the choice between the methods easier. …

… considerations, and assumptions of discriminant analysis and logistic regression. Further,
both … a brief comparison of discriminant analysis and logistic regression. Discriminant Analysis …

… techniques of discriminant analysis, logistic regression and classification tree (CT) analysis,
… the three methods is that discriminant analysis and logistic regression make a number of …

… fewer assumptions than discriminant analysis. Even when the assumptions required for
discriminant analysis are satisfied, logistic regression still performs well. In logistic regression, …

… : either to use a discriminant analysis or a logistic regression. Discriminant analysis is used
when the data are normally distributed whereas the logistic regression is used when the data …

… logistic regression and discriminant analysis. Because the ordinary least regression … be
categorical, the logistic regression and the discriminant analysis techniques are two major …

… discriminant analysis, based upon the Epanechnikov Kernel performed better than logistic
regression or parametric discriminant analysis. … than nonparametric discriminant analysis in …

… involved correctly applying logistic regression and discriminant analysis: we ensured, for …
and incorporation into principal components analysis prior to further analysis. We were also …