Optimal generalized logistic estimator

Nagarajah Varathan and Pushpakanthie Wijekoon

Communications in Statistics - Theory and Methods, 2018, vol. 47, issue 2, 463-474

Abstract: In this paper, we propose a new efficient estimator namely Optimal Generalized Logistic Estimator (OGLE) for estimating the parameter in a logistic regression model when there exists multicollinearity among explanatory variables. Asymptotic properties of the proposed estimator are also derived. The performance of the proposed estimator over the other existing estimators in respect of Scalar Mean Square Error criterion is examined by conducting a Monte Carlo simulation.

Date: 2018
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DOI: 10.1080/03610926.2017.1307406

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