INFERENCES IN LOGISTIC MODELS ALONG WITH ESTIMATION OF PARAMETERS USING DISCRIMINANT FUNCTION APPROACH

Parameter estimation in logistic regression using the maximum likelihood approach and the discriminant function approach is revisited. A bootstrap estimation of the standard errors for the estimates of the model parameters in discriminant function approach is obtained. The asymptotic distributions a...

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Bibliographic Details
Published in:Far East Journal of Theoretical Statistics 2012-04, Vol.39 (1), p.53-53
Main Authors: Rahman, Mezbahur, Holt, Katherine A, O'Connor, Patrick A
Format: Article
Language:English
Subjects:
Asymptotic properties
Far East
Logistics
Mathematical analysis
Mathematical models
Regression
Sampling
Statistics
Online Access:Get full text
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Summary:Parameter estimation in logistic regression using the maximum likelihood approach and the discriminant function approach is revisited. A bootstrap estimation of the standard errors for the estimates of the model parameters in discriminant function approach is obtained. The asymptotic distributions are compared in both the estimation procedures using bootstrap sampling. All the computations are performed for three different vastly used data sets and analyzed.
ISSN:0972-0863