Shrinkage estimators in zero-inflated Bell regression model with application

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Hauptverfasser: Seifollahi, Solmaz, Bevrani, Hossein, Algamal, Zakariya Yahya
Format: Preprint
Veröffentlicht: 2024
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author Seifollahi, Solmaz
Bevrani, Hossein
Algamal, Zakariya Yahya
author_facet Seifollahi, Solmaz
Bevrani, Hossein
Algamal, Zakariya Yahya
contents We propose Stein-type estimators for zero-inflated Bell regression models by incorporating information on model parameters. These estimators combine the advantages of unrestricted and restricted estimators. We derive the asymptotic distributional properties, including bias and mean squared error, for the proposed shrinkage estimators. Monte Carlo simulations demonstrate the superior performance of our shrinkage estimators across various scenarios. Furthermore, we apply the proposed estimators to analyze a real dataset, showcasing their practical utility.
format Preprint
id arxiv_https___arxiv_org_abs_2403_00749
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Shrinkage estimators in zero-inflated Bell regression model with application
Seifollahi, Solmaz
Bevrani, Hossein
Algamal, Zakariya Yahya
Computation
Statistics Theory
Applications
Methodology
62F12, 62F30, 62J12
We propose Stein-type estimators for zero-inflated Bell regression models by incorporating information on model parameters. These estimators combine the advantages of unrestricted and restricted estimators. We derive the asymptotic distributional properties, including bias and mean squared error, for the proposed shrinkage estimators. Monte Carlo simulations demonstrate the superior performance of our shrinkage estimators across various scenarios. Furthermore, we apply the proposed estimators to analyze a real dataset, showcasing their practical utility.
title Shrinkage estimators in zero-inflated Bell regression model with application
topic Computation
Statistics Theory
Applications
Methodology
62F12, 62F30, 62J12
url https://arxiv.org/abs/2403.00749