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Journal article

More on the restricted Liu estimator in the logistic regression model

Abstract

Şiray et al. proposed a restricted Liu estimator to overcome multicollinearity in the logistic regression model. They also used a Monte Carlo simulation to study the properties of the restricted Liu estimator. However, they did not present the theoretical result about the mean squared error properties of the restricted estimator compared to MLE, restricted maximum likelihood estimator (RMLE) and Liu estimator. In this article, we compare the restricted Liu estimator with MLE, RMLE and Liu estimator in the mean squared error sense and we also present a method to choose a biasing parameter. Finally, a real data example and a Monte Carlo simulation are conducted to illustrate the benefits of the restricted Liu estimator.

Authors

Wu J; Asar Y

Journal

Communications in Statistics - Simulation and Computation, Vol. 46, No. 5, pp. 3680–3689

Publisher

Taylor & Francis

Publication Date

May 28, 2017

DOI

10.1080/03610918.2015.1100735

ISSN

0361-0918
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