عنوان	Estimation of count parameters in zero-inflated Poisson regression model based on Stein-Liu estimators
نوع پژوهش	مقاله ارائه شده کنفرانسی
کلیدواژه‌ها	Monte Carlo simulation, Multicollinearity problem, Stein-Liu estimators, zero inflated Poisson model
چکیده	The ZIP regression is applied for modelling count data with extra zeros. In this paper, we have improved the count parameter estimation in this model with correlated count predictor variables under the assumption of sparseness of the model using Stein-Liu estimators. We have conducted a Monte Carlo simulation study for various combinations of sample sizes, inactive count predictor variables, and correlation level between the count predictor variables in order to compare the performance of the suggested estimator with the unrestricted Liu estimator in terms of simulated relative efficiency criteria. Our results showed that the performance of the Stein-Liu estimators is superior to the unrestricted Liu estimator in any situations.
پژوهشگران	زهرا زندی (نفر اول)، حسین بیورانی (Hossein Bevrani) (نفر دوم)