Article

Title: Liu-Type Multinomial Logistic Estimator

Issue: Volume 81 Series B Part 2 Year 2019
Pages: 203 -- 225
Abstract
Multicollinearity in multinomial logistic regression affects negatively on the variance of the maximum likelihood estimator. That leads to inflated confidence intervals and theoretically important variables become insignificant in testing hypotheses. In this paper, Liu-type estimator is proposed that has smaller total mean squared error than the maximum likelihood estimator. The proposed estimator is a general estimator which includes other biased estimators such as Liu estimator and ridge estimator as special cases. Simulation studies and an application are given to evaluate the performance of our estimator. The results indicate that the proposed estimator is more efficient and reliable than the conventional estimators.
Primary 62J07; Secondary 62J12.
Keywords and phrases: Liu estimator, Multicollinearity problem, Optimal shrinkage parameter, Ridge regression estimator, Stepwise method.