Simulation Study of Modified Two-Parameter Liu Estimator (MTPLE) Method to Overcome Multicollinearity in The Poisson Regression Model

Authors

  • Margeliza Safitri Department of Mathematics, University of Lampung, Indonesia
  • Netti Herawati Department of Mathematics, University of Lampung, Indonesia
  • Bernadhita Herindri Samodera Utami Department of Mathematics, University of Lampung, Indonesia
  • Subian Saidi Department of Mathematics, University of Lampung, Indonesia

DOI:

https://doi.org/10.5281/zenodo.14916371

Keywords:

Modified Two-Parameter Liu Estimator, Liu Estimator, Maximum Likelihood Estimator, Multicollinearity, Poisson Regression Model

Abstract

This study aims to evaluate the performance of the Modified Two-Parameter Liu Estimator method in dealing with multicollinearity and compare the performance of Maximum Likelihood Estimator, Liu Estimator, and Modified Two-Parameter Liu Estimator. Simulated data was used with n = 30, 50, 75, 150, and 300 in a Poisson regression model (p = 4, 6, 8) with ρ = 0.89, 0.95, and 0.99. The performance is evaluated using the mean square error criterion. The study results showed the superiority of Modified Two-Parameter Liu Estimator over the other estimators as it has the smallest mean square error value.

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References

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Published

2025-02-27

How to Cite

Safitri, M., Herawati, N., Utami, B. H. S., & Saidi, S. (2025). Simulation Study of Modified Two-Parameter Liu Estimator (MTPLE) Method to Overcome Multicollinearity in The Poisson Regression Model. International Journal of Scientific Research and Modern Technology, 4(2), 20–25. https://doi.org/10.5281/zenodo.14916371

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