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In the presence of multicollinearity in logistic regression, the variance of the Maximum Likelihood Estimator MLE becomes inflated. Siray et al. 2015 1 proposed a restricted Liu estimator in logistic regression model with exact linear restrictions. However, there are some situations, where the linear restrictions are stochastic. In this paper, we propose a Stochastic Restricted Maximum Likelihood Estimator SRMLE for the logistic regression model with stochastic linear restrictions to overcome this issue. Moreover, a Monte Carlo simulation is conducted for comparing the performances of the MLE, Restricted Maximum Likelihood Estimator RMLE, Ridge Type Logistic EstimatorLRE, Liu Type Logistic EstimatorLLE, and SRMLE for the logistic regression model by using Scalar Mean Squared Error SMSE.

KEYWORDS

Logistic Regression, Multicollinearity, Stochastic Restricted Maximum Likelihood Estimator, Scalar Mean Squared Error

Cite this paper

Nagarajah, V. and Wijekoon, P. 2015 Stochastic Restricted Maximum Likelihood Estimator in Logistic Regression Model. Open Journal of Statistics, 5, 837-851. doi: 10.4236-ojs.2015.57082.





Autor: Varathan Nagarajah1,2, Pushpakanthie Wijekoon3

Fuente: http://www.scirp.org/



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