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Journals / Hacettepe Journal of Mathematics and Statistics / 2026 / Volume: 48 Issue: 4

Restricted Liu estimator in generalized linear models: Monte Carlo simulation studies on gamma and Poisson distributed responses

Fikriye Kurtoğlu0000-0001-9956-7741
M. Revan Özkale0000-0001-7085-7403
Pages
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Publication Date
2019-08-08
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results are illustrated by conducting simulation studies and numerical examples.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, we introduce iterative restricted Liu estimator to combat multicollinearity in generalized linear models.
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Key Findings & Data:We also obtain necessary and sufficient conditions for the superiority of the first-order approximated restricted Liu estimator over the first-order approximated maximum likelihood and Liu estimators by the approximated mean squared error criterion.
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Conclusion & Impact:The results are illustrated by conducting simulation studies and numerical examples.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Restricted Liu estimation · Multicollinearity · Generalized linear models

Abstract

In this study, we introduce iterative restricted Liu estimator to combat multicollinearity in generalized linear models. We also obtain necessary and sufficient conditions for the superiority of the first-order approximated restricted Liu estimator over the first-order approximated maximum likelihood and Liu estimators by the approximated mean squared error criterion. The results are illustrated by conducting simulation studies and numerical examples.

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Cite This Article

Kurtoğlu, F., Özkale, M. R. (2019). Restricted Liu estimator in generalized linear models: Monte Carlo simulation studies on gamma and Poisson distributed responses. Hacettepe Journal of Mathematics and Statistics, Volume: 48 Issue: 4. https://ajindex.com/articles/1402777

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