期刊
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
卷 -, 期 -, 页码 -出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/03610918.2023.2179070
关键词
Multicollinearity; shrinkage parameters; ZINBLE; ZINBMRT; ZINBRE
The ZINB modified ridge type (ZINBMRT) estimator is proposed to address the issue of multicollinearity in the ZINB regression model. New approaches to estimate the shrinkage parameters for the ZINBMRT estimator are also proposed. Simulation and example studies show that the proposed ZINBMRT estimator outperforms other competitive estimators.
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.
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