Mohamed R. Abonazel
Associate Professor of Applied Statistics and Econometrics at Cairo University
5 Dr. Ahmed Zewail Street, Postal Code: 12613, Orman, Giza, Egypt (email)
A Comparative Study of Robust Estimators for Poisson Regression Model with Outliers
- Citation:
- Abonazel, M. R., and O. M. Saber, "A Comparative Study of Robust Estimators for Poisson Regression Model with Outliers", Journal of Statistics Applications and Probability, vol. 9, issue 2, pp. 279-286, 2020.
Abstract:
The present paper considers Poisson regression model in case of the dataset that contains outliers. The Monte Carlo simulation study was conducted to compare the robust (Mallows quasi-likelihood, weighted maximum likelihood) estimators with the nonrobust (maximum likelihood) estimator of this model with outliers. The simulation results showed that the robust estimators give better performance than maximum likelihood estimator, and the weighted maximum likelihood estimator is more efficient than Mallows quasi-likelihood estimator.