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Liu-Type Multinomial Logistic Estimator

Author

Listed:
  • Mohamed R. Abonazel

    (Cairo University)

  • Rasha A. Farghali

    (Helwan University)

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.

Suggested Citation

  • Mohamed R. Abonazel & Rasha A. Farghali, 2019. "Liu-Type Multinomial Logistic Estimator," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(2), pages 203-225, December.
    • Handle: RePEc:spr:sankhb:v:81:y:2019:i:2:d:10.1007_s13571-018-0171-4
    DOI: 10.1007/s13571-018-0171-4
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    References listed on IDEAS

    as
    1. Månsson, Kristofer & Kibria, B.M. Golam & Shukur, Ghazi, 2012. "On Liu estimators for the logit regression model," Economic Modelling, Elsevier, vol. 29(4), pages 1483-1488.
    2. Faisal Zahid & Gerhard Tutz, 2013. "Ridge estimation for multinomial logit models with symmetric side constraints," Computational Statistics, Springer, vol. 28(3), pages 1017-1034, June.
    3. Fatma Kurnaz & Kadri Akay, 2015. "A new Liu-type estimator," Statistical Papers, Springer, vol. 56(2), pages 495-517, May.
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