  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.
