A Comparison between Methods of Laplace Estimators and the Robust Huber for Estimate parameters logistic regression model - احمد ايمان حسن; شهاب ضمياء حامد (Journal of Economics and Administrative Sciences, 2017)
The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis . The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result. We will review in this research to estimate parameters of logistic regression model these methods are Laplace Estimators (LP-) and Huber estimator (H). Was conducted to compare between two methods through the simulation and using comparison criteria mean square error (MSE) for proportion different of contamination and sample sizes for determinant to reach the best method to estimate the parameter. It was found that method (H) is better in estimate parameters of logistic regression model.