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.

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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
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article

Robust Enhanced Ridge-Type Estimation for the Poisson Regression Models: Application to English League Football Data

Rasha A. Farghali, Adewale F. Lukman, Abiola T. Owolabi, Olukunmi Olatunji Akanni et al.
8 citations
International Journal of Uncertainty Fuzziness and Knowledge-Based Systems
Advanced Statistical Methods and Models
5.67
article

Robust Enhanced Ridge-Type Estimation for the Poisson Regression Models: Application to English League Football Data

Rasha A. Farghali, Adewale F. Lukman, Abiola T. Owolabi, Olukunmi Olatunji Akanni, Charles Kporxah
article en
8 citations

Abstract

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.

International Journal of Uncertainty Fuzziness and Knowledge-Based SystemsVol. 32(08)
University of North Dakota (US), Ladoke Akintola University of Technology (NG), Lead City University (NG), Helwan University (EG)
Openalex Percentile: Top 3%
Advanced Statistical Methods and Models
5.67
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