Evaluating the Performance of Liu Logistic Regression Estimator

Rasha A. Farghali ； Samah M. Abo-El-Hadid

《Research Journal of Mathematics and Statistics》 9卷2期 (2017/11) Pp. 11-19

https://doi.org/10.19026/rjms.9.4715

摘要

This study aims at comparing the performance of logistic Liu estimators with Maximum Likelihood (ML), Stien and ridge regression estimators using a Monte Carlo simulation, where the mean squared/absolute errors, MSE(β)/ MAE(β) mean squared/absolute error between the actual probability π(χ) and the estimated probability π(χ), MSE(π(χ))/ MAE(π(χ)) are used as performance criteria. An algorithm for simulation steps is included. An application of the effect of quantities of household wastes and its components on the probability of getting a running waste recycling factory is analyzed. Results from both the simulation and the application show that logistic Liu estimators are mostly preferred for correcting mutilcollinearity in logistic regression.

關鍵字

Biased estimators ； Liu estimators ； logistic regression ； multicollinearity ； ridge regression estimators ； stien estimators