Modified Ridge Estimator for Poisson Regression

Shuaib Mursal Ibrahim; Aydın Karakoca

doi:10.17776/csj.1372265

EN

Modified Ridge Estimator for Poisson Regression

Abstract

Poisson regression is a statistical model used to model the relationship between a count-valued-dependent variable and one or more independent variables. A frequently encountered problem when modeling such relationships is multicollinearity, which occurs when the independent variables are highly correlated with each other. Multicollinearity can affect the maximum likelihood (ML) estimates of unknown model parameters, making them unstable and inaccurate. In this study, we propose a modified ridge parameter estimator to combat multicollinearity in Poisson regression. We conducted extensive simulations to evaluate the performance of our proposed estimator using the mean squared error (MSE). We also apply our estimator to real data. The results show that our proposed estimator outperforms the ML estimator in both simulations and real data applications.

Keywords

References

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Details

Primary Language

English

Subjects

Applied Statistics

Journal Section

Research Article

Authors

Shuaib Mursal Ibrahim ^*
0000-0002-0258-034X
Türkiye

Aydın Karakoca
0000-0001-6503-3872
Türkiye

Publication Date

December 30, 2024

Submission Date

October 6, 2023

Acceptance Date

November 18, 2024

Published in Issue

Year 2024 Volume: 45 Number: 4

DOI

https://doi.org/10.17776/csj.1372265

IZ

https://izlik.org/JA64FC96WB

Cite

RIS / Bibtex

APA

Ibrahim, S. M., & Karakoca, A. (2024). Modified Ridge Estimator for Poisson Regression. Cumhuriyet Science Journal, 45(4), 811-822. https://doi.org/10.17776/csj.1372265

Öz

Modified Ridge Estimator for Poisson Regression

Abstract

Keywords

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite