Robust Enhanced Ridge-Type Estimation for the Poisson Regression Models: Application to English League Football Data
This study delves into the intricacies of addressing multicollinearity and outliers in Poisson regression modeling. Our examination encompasses a comprehensive survey of well-established methodologies, such as the ridge estimator and MT-estimator, and recent innovations like the enhanced ridge-type estimator. These approaches bolstered the robust estimation of the Poisson regression modeling with the development of a robust method. Through a series of numerical studies, including simulations and a meticulous analysis of the English League Football data, we empirically validate the efficacy of these methods. This research contributes to the evolving toolkit for effectively handling count data in the dynamic field of statistics.
Authors
- Rasha A. Farghali (ORCID: https://orcid.org/0000-0002-0506-5984)
- Adewale F. Lukman (ORCID: https://orcid.org/0000-0003-2881-1297)
- Abiola T. Owolabi (ORCID: https://orcid.org/0000-0001-9843-5085)
- Olukunmi Olatunji Akanni (ORCID: https://orcid.org/0000-0003-4108-6384)
- Charles Kporxah
Institutions
- University of North Dakota (US)
- Ladoke Akintola University of Technology (NG)
- Lead City University (NG)
- Helwan University (EG)
Publication Details
- Journal
- International Journal of Uncertainty Fuzziness and Knowledge-Based Systems
- Published
- 2024-11-01
- DOI
- https://doi.org/10.1142/s0218488524500284
- Citations
- 8
- Primary Topic
- Advanced Statistical Methods and Models
- Type
- article
- Field-Weighted Citation Impact
- 5.67