Abstract
The Zero-inflated negative binomial (ZINB) regression models are commonly used for count data that shows an over-dispersion and extra zeros. Multicollinearity is considered to be a significant issue in the estimation of parameters in the ZINB regression model. Thus, to alleviate the negative effects of multicollinearity, a new estimator called ZINB modified ridge type (ZINBMRT) estimator is proposed. Furthermore, we proposed some new approaches to estimate the shrinkage parameters for the ZINBMRT estimator. A Monte Carlo simulation study and illustrative example are given to show the superiority of the proposed ZINBMRT estimator over some of the existing estimation methods. Based on the findings of simulation study and example, it is observed that the proposed ZINBMRT estimator under different suggested parameters give a better performance over the other competitive estimators.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Communications in Statistics - Simulation and Computation
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.