عنوان	Improved Efficiency in Generalized Poisson Hurdle Model Estimation Using Restricted and Shrinkage Methods
نوع پژوهش	مقاله چاپ‌شده در مجلات علمی
کلیدواژه‌ها	Generalized Poisson hurdle regression, Monte Carlo simulation, overdispersion; preliminary test, shrinkage estimators
چکیده	This paper investigates the use of shrinkage estimators in the generalized Poisson hurdle (GPH) model for count data analysis. The GPH model effectively handles data with both excess zeros and over‐ or underdispersion. We propose shrinkage estimators to improve parameter estimation in this model and analyze their asymptotic properties, including biases and risks. An extensive comparison through Monte Carlo simulations evaluates the efficacy of the suggested estimators against the maximum likelihood estimator, employing a simulated relative efficiency criterion. In addition, we apply the estimators to two real‐world datasets. Our findings illustrate that the suggested shrinkage estimators yield superior results compared to the traditional maximum likelihood estimator.
پژوهشگران	حیدر حسن رحمه الغراوی (نفر اول)، حسین بیورانی (Hossein Bevrani) (نفر دوم)، بسیم شلیبه مسالم (نفر سوم)