Liu-Type Estimator in Inverse Gaussian Regression Model Based on (r-(k-d)) Class Estimator

Authors

Zeina Ameer Hadied, University of Mosul, Mosul, IraqFollow
Oday Esam Al-Saqal, Department of Sharia, University of Mosul, Mosul, IraqFollow
Zakariya Yahya Algamal, Department of Statistics and Informatics, University of Mosul, Mosul, IraqFollow

Abstract

When multicollinearity arises in the inverse Gaussian regression (IGR), there is a substantially unstable variance in the maximum likelihood estimator. Based on the (r-(k-d)) class estimation method, we present a novel Liu-type estimator in the IGR model in this study. The study examines the e ectiveness of the suggested estimator and draws comparisons with alternative estimators. Based on simulation and real data results, the suggested estimate performs better than the other estimators in terms of mean squared error.

Recommended Citation

Hadied, Zeina Ameer; Al-Saqal, Oday Esam; and Algamal, Zakariya Yahya (2025) "Liu-Type Estimator in Inverse Gaussian Regression Model Based on (r-(k-d)) Class Estimator," Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 1, Article 4.
DOI: https://doi.org/10.52866/2788-7421.1234
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss1/4