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Expected Error Rates for Logistic Regression Versus Normal Discriminant Analysis
Author(s) -
McLachlan G. J.,
Byth K.
Publication year - 1979
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710210107
Subject(s) - logistic regression , statistics , mathematics , normality , multivariate normal distribution , linear discriminant analysis , context (archaeology) , asymptotic distribution , covariance matrix , econometrics , multivariate statistics , covariance , logistic distribution , normal distribution , biology , paleontology , estimator
The expected error rates associated with using the allocation rule based on logistic regression are derived in the context of two multivariate normal populations with a common covariance matrix and compared with the corresponding error rates of the classical rule based on this normality assumption. It is shown in terms of the actual sizes of the asymptotic expected error rates that the performance of the logistic procedure does not fall far short of the normality based method, even for widely separated populations. This latter result is not obvious from previously available work on the asymptotic relative efficiency of the logistic procedure.