Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/6991
Title: A new kind of stochastic restricted biased estimator for logistic regression model
Authors: M. I. ALHEETY, Kristofer Månsson
B. M. Golam Kibria
Keywords: Logistic regression; maximum likelihood
estimator; mean squared error matrix; ridge regression;
Issue Date: 2020
Publisher: Journal of Applied Statistics
Abstract: In the logistic regression model, the variance of the maximum likelihood estimator is inflated and unstable when the multicollinearity exists in the data. There are several methods available in literature to overcome this problem. We propose a new stochastic restricted biased estimator. We study the statistical properties of the proposed estimator and compare its performance with some existing estimators in the sense of scalar mean squared criterion. An example and a simulation study are provided to illustrate the performance of the proposed estimator.
URI: http://localhost:8080/xmlui/handle/123456789/6991
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