Statistical Applications
Monday, September 22
An application of Liu-Type logistic estimators to the population data of Sweden Adnan Karaibrahimoglu and Yasin Asar Necmettin Erbakan University, Konya, Turkey
[email protected],
[email protected] Logistic regression methods have become an integral component of the data analysis concerned with the discrete binary or dichotomous outcome variable with many kinds of explanatory variables. It is known that the problem of multicollinearity affects the maximum likelihood estimator (MLE) negatively. Its variance is inflated and the estimations of the regression coefficients become unstable. In this study, we tried to get rid of this problem by using Liu-type logistic estimators with optimal shrinkage parameter and some existing ridge parameters. Thus, we designed a simulation study to evaluate the ridge regression parameters and determine the performances of the estimators. Moreover, we tried to model the data concerning the municipalities of Sweden. Since there exists a multicollinearity problem on the data, we used Liu-type logistic estimators in order to decrease the mean squared error (MSE) and overcome the multicollinearity problem.
Applied Statistics
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